50+ Remote Data Science Jobs in India

● Candidate should have Hands-on development experience as Data Analyst and/or ML Engineer.

● Candidate must have Coding experience in Python.

● Candidate should have Good Experience with ML models and ML algorithms.

● Need Experience with statistical modelling of large data sets.

● Looking for Immediate joiners or max. 30 days of Notice Period candidates.

● The candidates based out of these locations - Bangalore, Pune, Hyderabad, Mumbai, will be preffered.

What You will do:

● Play the role of Data Analyst / ML Engineer

● Collection, cleanup, exploration and visualization of data

● Perform statistical analysis on data and build ML models

● Implement ML models using some of the popular ML algorithms

● Use Excel to perform analytics on large amounts of data

● Understand, model and build to bring actionable business intelligence out of data that is available in different formats

● Work with data engineers to design, build, test and monitor data pipelines for ongoing business operations

Basic Qualifications:

● Experience: 4+ years.

● Hands-on development experience playing the role of Data Analyst and/or ML Engineer.

● Experience in working with excel for data analytics

● Experience with statistical modelling of large data sets

● Experience with ML models and ML algorithms

● Coding experience in Python

Nice to have Qualifications:

● Experience with wide variety of tools used in ML

● Experience with Deep learning

Benefits:

● Competitive salary.

● Hybrid work model.

● Learning and gaining experience rapidly.

● Reimbursement for basic working set up at home.

● Insurance (including a top up insurance for COVID).

Real-World Evidence (RWE) Analyst

Summary:

As an experienced Real-World Evidence (RWE) Analyst, you will leverage our cutting-edge healthcare data platform (accessing over 60 million lives in Asia, with ambitious growth plans across Africa and the Middle East) to deliver impactful clinical insights to our pharmaceutical clients. You will be involved in the full project lifecycle, from designing analyses to execution and delivery, within our agile data science team. This is an exciting opportunity to contribute significantly to a growing early-stage company focused on improving precision medicine and optimizing patient care for diverse populations.

Responsibilities:

·      Contribute to the design and execution of retrospective and prospective real-world research, including epidemiological and patient outcomes studies.

·      Actively participate in problem-solving discussions by clearly defining issues and proposing effective solutions.

·      Manage the day-to-day progress of assigned workstreams, ensuring seamless collaboration with the data engineering team on analytical requests.

·      Provide timely and clear updates on project status to management and leadership.

·      Conduct in-depth quantitative and qualitative analyses, driven by project objectives and your intellectual curiosity.

·      Ensure the quality and accuracy of analytical outputs, and contextualize findings by reviewing relevant published research.

·      Synthesize complex findings into clear and compelling presentations and written reports (e.g., slides, documents).

·      Contribute to the development of standards and best practices for future RWE analyses.

Requirements:

·      Undergraduate or post-graduate degree (MS or PhD preferred) in a quantitative analytical discipline such as Epidemiology, (Bio)statistics, Data Science, Engineering, Econometrics, or Operations Research.

·      8+ years of relevant work experience demonstrating:

o  Strong analytical and problem-solving capabilities.

o  Experience conducting research relevant to the pharmaceutical/biotech industry.

·      Proficiency in technical skills including SQL and at least one programming language (R, Python, or similar).

·      Solid understanding of the healthcare/medical and pharmaceutical industries.

·      Proven experience in managing workstream or project management activities.

·      Excellent written and verbal communication, and strong interpersonal skills with the ability to build collaborative partnerships.

·      Exceptional attention to detail.

·      Proficiency in Microsoft Office Suite (Excel, PowerPoint, Word).

Other Desirable Skills:

·      Demonstrated dedication to teamwork and the ability to collaborate effectively across different functions.

·      A strong desire to contribute to the growth and development of the RWE analytics function.

·      A proactive and innovative mindset with an entrepreneurial spirit, eager to take on a key role in a dynamic, growing company.

Pattern Agentix (patternagentix.com) is seeking a Graduate AI researcher and developer to create advanced multi-agent AI systems leveraging cutting-edge AI research and Retrieval-Augmented Generation (RAG) techniques. The ideal candidate should have a strong academic and research background in AI, demonstrated through published research papers, open-source contributions (e.g., GitHub).

Exposure to bioinformatics or some background in bioinformatics a plus.

Key Responsibilities

Conduct advanced AI research and apply findings to develop scalable multi-agent AI architectures.

Develop intelligent AI agents using modern frameworks  

Apply Retrieval-Augmented Generation (RAG) techniques to enhance agent capabilities.

Required Skills & Experience

Master’s or Ph.D. in AI, Machine Learning, Computer Science, or a related field with some exposure to bioinformatics. 

Strong AI research background, demonstrated through peer-reviewed publications in top-tier AI/ML conferences or journals (e.g., NeurIPS, ICML, AAAI, CVPR, ACL, etc.).

Proficiency in Python and experience with AI/ML frameworks (e.g., PyTorch, TensorFlow).

Experience with multi-agent AI systems and their architectural design.

Project Scope

The project involves developing a sophisticated multi-agent system that:

Leverages RAG for improved information retrieval and knowledge generation.

We are open on compensation models but compensation will be aligned to local norms. We would consider part time or full time.

Position Overview: We are looking for an experienced and highly skilled Data Architect to join our team and help design, implement, and optimize data systems that support high-end analytical solutions for our clients. As a Data Architect, you will work closely with clients to understand their business needs and translate them into robust, scalable, and efficient technical solutions. You will be responsible for end-to-end data modelling, integration workflows, and data transformation processes while ensuring security, privacy, and compliance.In this role, you will also leverage the latest advancements in artificial intelligence, machine learning, and large language models (LLMs) to deliver high-impact solutions that drive business success. The ideal candidate will have a deep understanding of data infrastructure, optimization techniques, and cost-effective data management

Key Responsibilities:

Customer Collaboration:

• Partner with clients to gather and understand their business

requirements, translating them into actionable technical specifications.

• Act as the primary technical consultant to guide clients through data challenges and deliver tailored solutions that drive value.
• 
  

Data Modeling & Integration:

• Design and implement scalable, efficient, and optimized data models to support business operations and analytical needs.
• Develop and maintain data integration workflows to seamlessly extract, transform, and load (ETL) data from various sources into data repositories.
• Ensure smooth integration between multiple data sources and platforms, including cloud and on-premise systems
• 
  

Data Processing & Optimization:

• Develop, optimize, and manage data processing pipelines to enable real-time and batch data processing at scale.
• Continuously evaluate and improve data processing performance, optimizing for throughput while minimizing infrastructure costs.
• 
  

Data Governance & Security:

• Implement and enforce data governance policies and best practices, ensuring data security, privacy, and compliance with relevant industry regulations (e.g., GDPR, HIPAA).
• Collaborate with security teams to safeguard sensitive data and maintain privacy controls across data environments.
• 
  

Cross-Functional Collaboration:

• Work closely with data engineers, data scientists, and business

analysts to ensure that the data architecture aligns with organizational objectives and delivers actionable insights.

• Foster collaboration across teams to streamline data workflows and optimize solution delivery.
• 
  

Leveraging Advanced Technologies:

• Utilize AI, machine learning models, and large language models (LLMs) to automate processes, accelerate delivery, and provide
• smart, data-driven solutions to business challenges.
• Identify opportunities to apply cutting-edge technologies to improve the efficiency, speed, and quality of data processing and analytics.
• 
  

Cost Optimization:

• Proactively manage infrastructure and cloud resources to optimize throughput while minimizing operational costs.
• Make data-driven recommendations to reduce infrastructure overhead and increase efficiency without sacrificing performance.
• 
  

Qualifications:

Experience:

• Proven experience (5+ years) as a Data Architect or similar role, designing and implementing data solutions at scale.
• Strong expertise in data modelling, data integration (ETL), and data transformation processes.
• Experience with cloud platforms (AWS, Azure, Google Cloud) and big data technologies (e.g., Hadoop, Spark).
• 
  

Technical Skills:

• Advanced proficiency in SQL, data modelling tools (e.g., Erwin,PowerDesigner), and data integration frameworks (e.g., Apache
• NiFi, Talend).
• Strong understanding of data security protocols, privacy regulations, and compliance requirements.
• Experience with data storage solutions (e.g., data lakes, data warehouses, NoSQL, relational databases).
• 
  

AI & Machine Learning Exposure:

• Familiarity with leveraging AI and machine learning technologies (e.g., TensorFlow, PyTorch, scikit-learn) to optimize data processing and analytical tasks.
• Ability to apply advanced algorithms and automation techniques to improve business processes.
• 
  

 Soft Skills:

• Excellent communication skills to collaborate with clients, stakeholders, and cross-functional teams.
• Strong problem-solving ability with a customer-centric approach to solution design.
• Ability to translate complex technical concepts into clear, understandable terms for non-technical audiences.
• 
  

Education:

Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Science, or a related field (or equivalent practical experience).

LIFE AT FOUNTANE:

• Fountane offers an environment where all members are supported, challenged, recognized & given opportunities to grow to their fullest potential.
• Competitive pay
• Health insurance for spouses, kids, and parents.
• PF/ESI or equivalent
• Individual/team bonuses
• Employee stock ownership plan
• Fun/challenging variety of projects/industries
• Flexible workplace policy - remote/physical
• Flat organization - no micromanagement
• Individual contribution - set your deadlines
• Above all - culture that helps you grow exponentially!

A LITTLE BIT ABOUT THE COMPANY:

Established in 2017, Fountane Inc is a Ventures Lab incubating and investing in new competitive technology businesses from scratch. Thus far, we’ve created half a dozen multi-million valuation companies in the US and a handful of sister ventures for large corporations, including Target, US Ventures, and Imprint Engine.

We’re a team of 120+ strong from around the world that are radically open-minded and believes in excellence, respecting one another, and pushing our boundaries to the furthest it's ever been.

We are seeking a highly skilled and experienced Senior Data Scientist to join our growing data science team. In this role, you will lead complex data analysis projects, develop advanced machine learning models, and provide actionable insights that drive strategic business decisions. You will mentor junior data scientists and collaborate with cross-functional teams to solve challenging problems and improve our products and services.

Responsibilities:

• Lead and execute end-to-end data science projects: From problem definition and data collection to model development, evaluation, and deployment.
• Develop and implement advanced machine learning models: Including but not limited to regression, classification, clustering, deep learning, and natural language processing.
• Perform complex data analysis and statistical modeling: To identify trends, patterns, and insights from large datasets.
• Design and implement data pipelines and ETL processes: To ensure data quality and accessibility.
• Communicate findings and recommendations effectively: Through visualizations, reports, and presentations to both technical and non-technical audiences.
• Collaborate with cross-functional teams: Including product managers, engineers, and business stakeholders, to define project goals and deliver impactful solutions.
• Mentor and guide junior data scientists: Providing technical expertise and fostering a collaborative learning environment.
• Stay up-to-date with the latest advancements in data science and machine learning: And apply new techniques and technologies to improve our data science capabilities.
• Contribute to the development of best practices and standards: For data science methodologies and tools.
• Evaluate and improve existing models and algorithms: to maximize performance and accuracy.

We are seeking a talented and passionate Data Scientist to join our dynamic team. The ideal candidate will leverage their expertise in statistical analysis, machine learning, and data visualization to extract actionable insights from complex datasets. You will play a key role in developing and deploying predictive models, contributing to strategic business decisions, and driving innovation through data.

Responsibilities:

• Data Analysis and Exploration:
• Collect, clean, and preprocess large datasets from various sources.
• Conduct exploratory data analysis to identify patterns, trends, and anomalies.
• Visualize data using appropriate tools and techniques to communicate findings effectively.
• Machine Learning and Modeling:
• Develop and implement machine learning models for predictive analytics, classification, regression, and clustering.
• Evaluate model performance and optimize algorithms for accuracy and efficiency.
• Stay up-to-date with the latest advancements in machine learning and artificial intelligence.
• Statistical Analysis:
• Perform statistical hypothesis testing and A/B testing to validate findings.
• Apply statistical methods to analyze data and draw meaningful conclusions.
• Develop statistical models to forecast future trends and outcomes.
• Data Visualization and Reporting:
• Create compelling visualizations and dashboards to present data insights to stakeholders.
• Prepare clear and concise reports summarizing findings and recommendations.
• Effectively communicate complex data concepts to non-technical audiences.
• Collaboration and Communication:
• Collaborate with cross-functional teams, including engineers, product managers, and business analysts.
• Present findings and recommendations to stakeholders at all levels of the organization.
• Contribute to the development of data-driven strategies and initiatives.

We are seeking a talented and passionate Data Scientist to join our dynamic team. The ideal candidate will leverage advanced statistical and machine learning techniques to extract actionable insights from complex datasets, driving strategic business decisions and product development. You will work closely with cross-functional teams, including engineers, product managers, and business stakeholders, to solve challenging problems and contribute to our data-driven culture.

Responsibilities:

• Data Analysis & Modeling:
• Develop and implement advanced statistical models, machine learning algorithms, and deep learning techniques to solve complex business problems.
• Perform exploratory data analysis (EDA) to identify patterns, trends, and anomalies in large datasets.
• Build and evaluate predictive models for forecasting, classification, and regression tasks.
• Utilize statistical hypothesis testing and A/B testing to validate hypotheses and measure the impact of changes.
• Data Engineering & Management:
• Collaborate with data engineers to ensure data quality, integrity, and accessibility.
• Extract, transform, and load (ETL) data from various sources into usable formats.
• Develop and maintain data pipelines for efficient data processing and analysis.
• Work with large datasets and distributed computing frameworks (e.g., Spark, Hadoop).
• Communication & Visualization:
• Communicate complex data insights and findings to technical and non-technical audiences through clear visualizations and reports.

Key Responsibilities:

• Data Collection and Preparation:
• Gathering data from various sources (databases, APIs, files).
• Cleaning and preprocessing data (handling missing values, outliers, inconsistencies).
• Transforming data into a suitable format for analysis.
• Data Analysis:
• Performing exploratory data analysis (EDA) to identify patterns and trends.
• Applying statistical techniques and machine learning algorithms.
• Creating data visualizations (charts, graphs) to communicate findings.
• Model Development and Evaluation:
• Assisting in the development and training of machine learning models.
• Evaluating model performance using appropriate metrics.
• Contributing to model tuning and optimization.

We are looking for a motivated Junior Data Scientist to join our data science team. The ideal candidate will have a passion for analyzing data, building predictive models, and extracting actionable insights to solve business challenges. You will work with senior data scientists and cross-functional teams to develop data-driven solutions and contribute to the organization’s decision-making processes.

Key Responsibilities:

• Assist in data collection, cleaning, and preprocessing to ensure high-quality datasets for analysis.
• Perform exploratory data analysis (EDA) to identify trends, patterns, and relationships in large datasets.
• Develop and implement machine learning models to solve business problems, such as classification, regression, or clustering tasks.
• Collaborate with senior data scientists to design experiments, evaluate models, and refine predictive algorithms.
• Conduct statistical analysis and hypothesis testing to validate model assumptions and results.
• Visualize and communicate insights from data analysis in a clear and actionable manner using data visualization tools (e.g., Matplotlib, Tableau, Power BI).
• Support the team in deploying machine learning models into production and maintaining them.
• Stay up-to-date with the latest data science trends, tools, and techniques to contribute to continuous improvement.

Key Responsibilities:

• Collect, clean, and preprocess structured and unstructured data for analysis.
• Develop predictive models and machine learning algorithms to solve business problems.
• Use statistical and analytical techniques to extract insights and trends from large datasets.
• Work with engineering teams to deploy machine learning models into production.
• Design and implement A/B tests to measure the impact of changes and improvements.
• Create data visualizations and reports to communicate insights to stakeholders.
• Collaborate with product, marketing, and operations teams to drive data-driven strategies.
• Stay up to date with the latest advancements in data science and machine learning.

Required Qualifications:

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, or a related field.
• Experience with programming languages such as Python, R, or SQL.
• Proficiency in machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
• Strong knowledge of data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn).
• Experience with cloud platforms like AWS, GCP, or Azure is a plus.
• Understanding of big data technologies (e.g., Spark, Hadoop) is a bonus.

Data Collection and Preprocessing:

• Gather and clean data from various sources (e.g., databases, APIs, web scraping).
• Perform data validation and ensure data quality.
• Transform and prepare data for analysis and modeling.

Data Analysis and Modeling:

• Conduct exploratory data analysis (EDA) to identify patterns and trends.
• Develop and implement machine learning models (e.g., regression, classification, clustering).
• Evaluate model performance and optimize for accuracy and efficiency.
• Apply statistical techniques and algorithms to solve business problems.

Data Visualization and Reporting:

• Create compelling visualizations to communicate insights to stakeholders.
• Develop dashboards and reports to track key performance indicators (KPIs).
• Present findings to technical and non-technical audiences.

Core Responsibilities:

• Data Collection and Preprocessing:
• Gathering data from various sources (databases, APIs, web scraping, etc.).
• Cleaning and transforming raw data into a usable format.
• Handling missing values, outliers, and inconsistencies.
• Exploratory Data Analysis (EDA):
• Analyzing data to identify patterns, trends, and relationships.
• Using statistical methods and visualization techniques to gain insights.
• Formulating hypotheses and identifying potential areas of investigation.
• Model Development and Implementation:
• Developing machine learning models for prediction, classification, and clustering.
• Selecting appropriate algorithms and techniques based on the problem and data.
• Training, testing, and evaluating model performance.
• Deploying models into production environments.
• Data Visualization and Communication:
• Creating clear and concise visualizations to communicate findings to stakeholders.
• Presenting data-driven insights and recommendations to both technical and non-technical audiences.
• Writing reports and documentation to summarize analysis and results.

Machine Learning and Predictive Modeling:

• Developing and implementing machine learning models for prediction, classification, and clustering.
• Selecting appropriate algorithms and techniques based on the problem and data.
• Evaluating model performance and optimizing for accuracy.

Data Visualization and Communication:

• Creating clear and concise visualizations to communicate insights to stakeholders.
• Presenting findings and recommendations to both technical and non-technical audiences.
• Translating complex data into actionable business strategies.

Collaboration and Problem-Solving:

• Working closely with cross-functional teams to understand business needs.
• Identifying and solving complex business problems using data-driven approaches.
• Staying up-to-date with the latest advancements in data science and machine learning.

Data Analysis and Interpretation:

• Analyze data using statistical methods and tools (e.g., SQL, Python, R).
• Identify trends, patterns, and correlations in complex datasets.
• Perform exploratory data analysis to uncover insights.
• Conduct hypothesis testing and statistical analysis.

Data Visualization and Reporting:

• Create visually appealing and informative reports and dashboards.
• Use data visualization tools (e.g., Tableau, Power BI) to present findings.
• Communicate insights and recommendations to stakeholders in a clear and concise manner.
• Prepare reports for internal or external audiences using business analytics reporting tools containing graphs, charts, and other visual aids.

Data Scientists are analytical experts who use their skills in mathematics, statistics, and computer science to solve complex business problems. They collect, analyze, and interpret large datasets to extract meaningful insights and develop data-driven solutions. Their work helps organizations make informed decisions, improve processes, and gain a competitive edge.

Key Responsibilities:

• Data Collection and Preprocessing:
• Gathering data from various sources (databases, APIs, web scraping, etc.).
• Cleaning and transforming data to ensure quality and consistency.
• Handling missing values, outliers, and inconsistencies.
• Integrating data from multiple sources.
• Data Analysis and Exploration:
• Conducting exploratory data analysis (EDA) to identify patterns, trends, and relationships.
• Applying statistical methods and hypothesis testing to validate findings.
• Visualizing data using charts, graphs, and other tools to communicate insights.
• Model Development and Deployment:
• Developing and implementing machine learning models (e.g., regression, classification, clustering, deep learning).
• Evaluating model performance and fine-tuning parameters.
• Deploying models into production environments.
• Creating and maintaining machine learning pipelines.
• Communication and Collaboration:
• Presenting findings and recommendations to stakeholders in a clear and concise manner.
• Collaborating with cross-functional teams (e.g., engineers, product managers, business analysts).
• Documenting code, models, and processes.
• Translating business requirements into technical implementations.

Data Collection and Preparation:

• Gathering data from various sources, including databases, APIs, and files.
• Cleaning, transforming, and pre-processing data to ensure quality and consistency.
• Developing and maintaining data pipelines.

Data Analysis and Modeling:

• Conducting exploratory data analysis (EDA) to identify patterns and trends.
• Developing and implementing statistical models and machine learning algorithms.
• Evaluating model performance and fine-tuning parameters.

Data Visualization and Communication:

• Creating visualizations (charts, graphs, dashboards) to communicate insights effectively.
• Presenting findings to stakeholders, including non-technical audiences.
• Translating data-driven insights into actionable recommendations.

Problem Solving and Business Understanding:

• Identifying business problems that can be addressed with data analysis.
• Working with stakeholders to define project goals and requirements.
• Applying data science techniques to solve real-world business challenges.

We are seeking an experienced Data Scientist to join our data-driven team. As a Data Scientist, you will work with large datasets, apply advanced analytics techniques, and build machine learning models to provide actionable insights that drive business decisions. You will collaborate with various teams to translate complex data into clear recommendations and innovative solutions.

Key Responsibilities:

• Analyze large datasets to identify trends, patterns, and insights that can inform business strategy.
• Develop, implement, and maintain machine learning models and algorithms to solve complex problems.
• Work closely with stakeholders to understand business objectives and translate them into data science tasks.
• Preprocess, clean, and organize raw data from various sources for analysis.
• Conduct statistical analysis and build predictive models to support data-driven decision-making.
• Create data visualizations and reports to communicate findings clearly and effectively to both technical and non-technical teams.
• Design experiments and A/B testing to evaluate business initiatives.
• Ensure the scalability and performance of data pipelines and machine learning models.
• Collaborate with engineering teams to integrate data science solutions into production systems.
• Continuously stay updated with the latest developments in data science, machine learning, and analytics technologies.

We are seeking a highly skilled and experienced Senior Data Analyst to join our team. In this role, you will be responsible for analyzing complex datasets, generating actionable insights, and supporting strategic decision-making processes. You will collaborate with cross-functional teams, develop data models, and create compelling reports and visualizations to communicate findings effectively.

Key Responsibilities:

• Data Analysis: Perform in-depth analysis of large datasets to identify trends, patterns, and correlations. Utilize statistical methods and data mining techniques to extract actionable insights.
• Reporting & Visualization: Develop and deliver comprehensive reports and interactive dashboards that effectively communicate data insights and business performance to stakeholders.
• Data Modeling: Build and maintain data models that support business operations and decision-making processes. Conduct data validation and ensure accuracy and consistency.
• Business Intelligence: Collaborate with business leaders and teams to understand their data needs and translate them into analytical requirements. Provide data-driven recommendations to support strategic initiatives.

About the Role

We are actively seeking talented Senior Python Developers to join our ambitious team dedicated to pushing the frontiers of AI technology. This opportunity is tailored for professionals who thrive on developing innovative solutions and who aspire to be at the forefront of AI advancements. You will work with different companies in the US who are looking to develop both commercial and research AI solutions.

Required Skills:

• Write effective Python code to tackle complex issues
• Use business sense and analytical abilities to glean valuable insights from public databases 
• Clearly express the reasoning and logic when writing code in Jupyter notebooks or other suitable mediums
• Extensive experience working with Python 
• Proficiency with the language's syntax and conventions
• Previous experience tackling algorithmic problems
• Nice to have some prior Software Quality Assurance and Test Planning experience
• Excellent spoken and written English communication skills

The ideal candidates should be able to

• Clearly explain their strategies for problem-solving.
• Design practical solutions in code.
• Develop test cases to validate their solutions.
• Debug and refine their solutions for improvement.

About the Company :

Nextgen Ai Technologies is at the forefront of innovation in artificial intelligence, specializing in developing cutting-edge AI solutions that transform industries. We are committed to pushing the boundaries of AI technology to solve complex challenges and drive business success.

Currently offering "Data Science Internship" for 2 months.

Data Science Projects details In which Intern’s Will Work :

Project 01 : Image Caption Generator Project in Python

Project 02 : Credit Card Fraud Detection Project

Project 03 : Movie Recommendation System

Project 04 : Customer Segmentation

Project 05 : Brain Tumor Detection with Data Science

Eligibility

A PC or Laptop with decent internet speed.

Good understanding of English language.

Any Graduate with a desire to become a web developer. Freshers are welcomed.

Knowledge of HTML, CSS and JavaScript is a plus but NOT mandatory.

Fresher are welcomed. You will get proper training also, so don't hesitate to apply if you don't have any coding background.

#please note that THIS IS AN INTERNSHIP , NOT A JOB.

We recruit permanent employees from inside our interns only (if needed).

Duration : 02 Months 

MODE: Work From Home (Online)

Responsibilities

Manage reports and sales leads in salesforce.com, CRM.

Develop content, manage design, and user access to SharePoint sites for customers and employees.

Build data driven reports, store procedures, query optimization using SQL and PL/SQL knowledge.

Learned the essentials to C++ and Java to refine code and build the exterior layer of web pages.

Configure and load xml data for the BVT tests.

Set up a GitHub page.

Develop spark scripts by using Scala shell as per requirements.

Develop and A/B test improvements to business survey questions on iOS.

Deploy statistical models to various company data streams using Linux shells.

Create monthly performance-base client billing reports using MySQL and NoSQL databases.

Utilize Hadoop and MapReduce to generate dynamic queries and extract data from HDFS.

Create source code utilizing JavaScript and PHP language to make web pages functional.

Excellent problem-solving skills and the ability to work independently or as part of a team.

Effective communication skills to convey complex technical concepts.

Benefits

Internship Certificate

Letter of recommendation

Stipend Performance Based

Part time work from home (2-3 Hrs per day)

5 days a week, Fully Flexible Shift

We are working on AI for medical images. We need someone who can run pre trained models and also train new ones

In this position, you will play a pivotal role in collaborating with our CFO, CTO, and our dedicated technical team to craft and develop cutting-edge AI-based products.

Role and Responsibilities:

- Develop and maintain Python-based software applications.

- Design and work with databases using SQL.

- Use Django, Streamlit, and front-end frameworks like Node.js and Svelte for web development.

- Create interactive data visualizations with charting libraries.

- Collaborate on scalable architecture and experimental tech. - Work with AI/ML frameworks and data analytics.

- Utilize Git, DevOps basics, and JIRA for project management. Skills and Qualifications:

- Strong Python programming

skills.

- Proficiency in OOP and SQL.

- Experience with Django, Streamlit, Node.js, and Svelte.

- Familiarity with charting libraries.

- Knowledge of AI/ML frameworks.

- Basic Git and DevOps understanding.

- Effective communication and teamwork.

Company details: We are a team of Enterprise Transformation Experts who deliver radically transforming products, solutions, and consultation services to businesses of any size. Our exceptional team of diverse and passionate individuals is united by a common mission to democratize the transformative power of AI.

Website: Blue Hex Software – AI | CRM | CXM & DATA ANALYTICS

Responsibilities

> Selecting features, building and optimizing classifiers using machine

> learning techniques

> Data mining using state-of-the-art methods

> Extending company’s data with third party sources of information when

> needed

> Enhancing data collection procedures to include information that is

> relevant for building analytic systems

> Processing, cleansing, and verifying the integrity of data used for

> analysis

> Doing ad-hoc analysis and presenting results in a clear manner

> Creating automated anomaly detection systems and constant tracking of

> its performance

Key Skills

> Hands-on experience of analysis tools like R, Advance Python

> Must Have Knowledge of statistical techniques and machine learning

> algorithms

> Artificial Intelligence

> Understanding of Text analysis- Natural Language processing (NLP)

> Knowledge on Google Cloud Platform

> Advanced Excel, PowerPoint skills

> Advanced communication (written and oral) and strong interpersonal

> skills

> Ability to work cross-culturally

> Good to have Deep Learning

> VBA and visualization tools like Tableau, PowerBI, Qliksense, Qlikview

> will be an added advantage

CTC Budget: 35-55LPA

Location: Hyderabad (Remote after 3 months WFO)

Company Overview:

An 8-year-old IT Services and consulting company based in Hyderabad providing services in maximizing product value while delivering rapid incremental innovation, possessing extensive SaaS company M&A experience including 20+ closed transactions on both the buy and sell sides. They have over 100 employees and looking to grow the team.

• 6 plus years of experience as a Python developer.
• Experience in web development using Python and Django Framework.
• Experience in Data Analysis and Data Science using Pandas, Numpy and Scifi-Kit - (GTH)
• Experience in developing User Interface using HTML, JavaScript, CSS.
• Experience in server-side templating languages including Jinja 2 and Mako
• Knowledge into Kafka and RabitMQ (GTH)
• Experience into Docker, Git and AWS
• Ability to integrate multiple data sources into a single system.
• Ability to collaborate on projects and work independently when required.
• DB (MySQL, Postgress, SQL)

Selection Process: 2-3 Interview rounds (Tech, VP, Client)

• Work closely with your business to identify issues and use data to propose solutions for effective decision making
• Build algorithms and design experiments to merge, manage, interrogate and extract data to supply tailored reports to colleagues, customers or the wider organisation.
• Creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc
• Querying databases and using statistical computer languages: R, Python, SLQ, etc.
• Visualizing/presenting data through various Dashboards for Data Analysis, Using Python Dash, Flask etc.
• Test data mining models to select the most appropriate ones for use on a project
• Work in a POSIX/UNIX environment to run/deploy applications
• Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
• Develop custom data models and algorithms to apply to data sets.
• Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
• Assess the effectiveness of data sources and data-gathering techniques and improve data collection methods
• Horizon scan to stay up to date with the latest technology, techniques and methods
• Coordinate with different functional teams to implement models and monitor outcomes.
• Stay curious and enthusiastic about using algorithms to solve problems and enthuse others to see the benefit of your work.

• Able to create algorithms to extract information from large data sets
• Strong knowledge of Python, R, Java or another scripting/statistical languages to automate data retrieval, manipulation and analysis.
• Experience with extracting and aggregating data from large data sets using SQL or other tools
• Strong understanding of various NLP, and NLU techniques like Named Entity Recognition, Summarization, Topic Modeling, Text Classification, Lemmatization and Stemming.
• Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, etc.
• Experience with Python libraries such as Pandas, NumPy, SciPy, Scikit-Learn
• Experience with Jupyter / Pandas / Numpy to manipulate and analyse data
• Knowledge of Machine Learning techniques and their respective pros and cons
• Strong Knowledge of various Data Science Visualization Tools like Tableau, PowerBI, D3, Plotly, etc.
• Experience using web services: Redshift, AWS, S3, Spark, DigitalOcean, etc.
• Proficiency in using query languages, such as SQL, Spark DataFrame API, etc.
• Hands-on experience in HTML, CSS, Bootstrap, JavaScript, AJAX, jQuery and Prototyping.
• Hands-on experience on C#, Javascript, .Net
• Experience in understanding and analyzing data using statistical software (e.g., Python, R, KDB+ and other relevant libraries)
• Experienced in building applications that meet enterprise needs – secure, scalable, loosely coupled design
• Strong knowledge of computer science, algorithms, and design patterns
• Strong oral and written communication, and other soft skills critical to collaborating and engage with teams

Role : 

• Understand and translate statistics and analytics to address business problems
• Responsible for helping in data preparation and data pull, which is the first step in machine learning
• Should be able to do cut and slice data to extract interesting insights from the data
• Model development for better customer engagement and retention
• Hands on experience in relevant tools like SQL(expert), Excel, R/Python
• Working on strategy development to increase business revenue

Requirements:

• Hands on experience in relevant tools like SQL(expert), Excel, R/Python
• Statistics: Strong knowledge of statistics
• Should able to do data scraping & Data mining
• Be self-driven, and show ability to deliver on ambiguous projects
• An ability and interest in working in a fast-paced, ambiguous and rapidly-changing environment
• Should have worked on Business Projects for an organization, Ex: customer acquisition, Customer retention.

Skills: Machine Learning,Deep Learning,Artificial Intelligence,python.

Location:Chennai


Domain knowledge: Data cleaning, modelling, analytics, statistics, machine learning, AI

Requirements:

·         To be part of Digital Manufacturing and Industrie 4.0 projects across Saint Gobain group of companies

·         Design and develop AI//ML models to be deployed across SG factories

·         Knowledge on Hadoop, Apache Spark, MapReduce, Scala, Python programming, SQL and NoSQL databases is required

·         Should be strong in statistics, data analysis, data modelling, machine learning techniques and Neural Networks

·         Prior experience in developing AI and ML models is required

·         Experience with data from the Manufacturing Industry would be a plus

Roles and Responsibilities:

·         Develop AI and ML models for the Manufacturing Industry with a focus on Energy, Asset Performance Optimization and Logistics

·         Multitasking, good communication necessary

·         Entrepreneurial attitude.

Job Responsibilities:-

• Develop robust, scalable and maintainable machine learning models to answer business problems against large data sets.
• Build methods for document clustering, topic modeling, text classification, named entity recognition, sentiment analysis, and POS tagging.
• Perform elements of data cleaning, feature selection and feature engineering and organize experiments in conjunction with best practices.
• Benchmark, apply, and test algorithms against success metrics. Interpret the results in terms of relating those metrics to the business process.
• Work with development teams to ensure models can be implemented as part of a delivered solution replicable across many clients.
• Knowledge of Machine Learning, NLP, Document Classification, Topic Modeling and Information Extraction with a proven track record of applying them to real problems.
• Experience working with big data systems and big data concepts.
• Ability to provide clear and concise communication both with other technical teams and non-technical domain specialists.
• Strong team player; ability to provide both a strong individual contribution but also work as a team and contribute to wider goals is a must in this dynamic environment.
• Experience with noisy and/or unstructured textual data.

knowledge graph and NLP including summarization, topic modelling etc

• Strong coding ability with statistical analysis tools in Python or R, and general software development skills (source code management, debugging, testing, deployment, etc.)
• Working knowledge of various text mining algorithms and their use-cases such as keyword extraction, PLSA, LDA, HMM, CRF, deep learning & recurrent ANN, word2vec/doc2vec, Bayesian modeling.
• Strong understanding of text pre-processing and normalization techniques, such as tokenization,
• POS tagging and parsing and how they work at a low level.
• Excellent problem solving skills.
• Strong verbal and written communication skills
• Masters or higher in data mining or machine learning; or equivalent practical analytics / modelling experience
• Practical experience in using NLP related techniques and algorithms
• Experience in open source coding and communities desirable.

Able to containerize Models and associated modules and work in a Microservices environment

About LodgIQ

LodgIQ is led by a team of experienced hospitality technology experts, data scientists and product domain experts. Seed funded by Highgate Ventures, a venture capital platform focused on early stage technology investments in the hospitality industry and Trilantic Capital Partners, a global private equity firm, LodgIQ has made a significant investment in advanced machine learning platforms and data science.

Title : Data Scientist

• Apply Data Science and Machine Learning to a REAL-LIFE  problem  - “Predict Guest Arrivals and Determine Best Prices for Hotels”
• Apply advanced analytics in a BIG Data Environment – AWS, MongoDB, SKLearn
• Help scale up the product in a global offering across 100+  global markets

• Minimum 3 years of experience with advanced data analytic techniques, including data mining, machine learning, statistical analysis, and optimization.    Student projects are acceptable.
• At least 1 year of experience with Python / Numpy / Pandas / Scipy/ MatPlotLib / Scikit-Learn
•   Experience in working with massive data sets, including structured and unstructured with at least 1 prior engagement involving data gathering, data cleaning, data mining, and data visualization
•   Solid grasp over  optimization techniques
•   Master's  or PhD degree in Business Analytics.  Data science, Statistics or Mathematics
•   Ability to show a track record of solving large, complex problems

• 6+ years Experienced in building data pipelines and deployment pipelines for machine learning models
• 4+ years’ experience with ML/AI toolkits such as Tensorflow, Keras, AWS Sagemaker, MXNet, H20, etc.
• 4+ years’ experience developing ML/AI models in Python/R
• Must have leadership abilities to lead a project and team.
• Must have leadership skills to lead and deliver projects, be proactive, take ownership, interface with business, represent the team and spread the knowledge.
• Strong knowledge of statistical data analysis and machine learning techniques (e.g., Bayesian, regression, classification, clustering, time series, deep learning).
• Should be able to help deploy various models and tune them for better performance.
• Working knowledge in operationalizing models in production using model repositories, API s and data pipelines.
• Experience with machine learning and computational statistics packages.
• Experience with Data Bricks, Data Lake.
• Experience with Dremio, Tableau, Power Bi.
• Experience working with spark ML, spark DL with Pyspark would be a big plus!
• Working knowledge of relational database systems like SQL Server, Oracle.
• Knowledge of deploying models in platforms like PCF, AWS, Kubernetes.
• Good knowledge in Continuous integration suites like Jenkins.
• Good knowledge in web servers (Apache, NGINX).
• Good knowledge in Git, Github, Bitbucket.
• Working knowledge in operationalizing models in production using model repositories, APIs and data pipelines.
• Java, R, and Python programming experience.
• Should be very familiar with (MS SQL, Teradata, Oracle, DB2).
• Big Data – Hadoop.
• Expert knowledge using BI tools e.g.Tableau
• Experience with machine learning and computational statistics packages.

Responsibilities: 

• Improve robustness of Leena AI current NLP stack 
• Increase zero shot learning capability of Leena AI current NLP stack 
• Opportunity to add/build new NLP architectures based on requirements 
• Manage End to End lifecycle of the data in the system till it achieves more than 90% accuracy 
• Manage a NLP team 

Page BreakRequirements: 

• Strong understanding of linear algebra, optimisation, probability, statistics 
• Experience in the data science methodology from exploratory data analysis, feature engineering, model selection, deployment of the model at scale and model evaluation 
• Experience in deploying NLP architectures in production 
• Understanding of latest NLP architectures like transformers is good to have 
• Experience in adversarial attacks/robustness of DNN is good to have 
• Experience with Python Web Framework (Django), Analytics and Machine Learning frameworks like Tensorflow/Keras/Pytorch. 

PriceLabs (https://www.chicagobusiness.com/innovators/what-if-you-could-adjust-prices-meet-demand" target="_blank">chicagobusiness.com/innovators/what-if-you-could-adjust-prices-meet-demand) is a cloud based software for vacation and short term rentals to help them dynamically manage prices just the way large hotels and airlines do! Our mission is to help small businesses in the travel and tourism industry by giving them access to advanced analytical systems that are often restricted to large companies. 

We're looking for someone with strong analytical capabilities who wants to understand how our current architecture and algorithms work, and help us design and develop long lasting solutions to address those. Depending on the needs of the day, the role will come with a good mix of team-work, following our best practices, introducing us to industry best practices, independent thinking, and ownership of your work.

Responsibilities:

• Design, develop and enhance our pricing algorithms to enable new capabilities.
• Process, analyze, model, and visualize findings from our market level supply and demand data.
• Build and enhance internal and customer facing dashboards to better track metrics and trends that help customers use PriceLabs in a better way.
• Take ownership of product ideas and design discussions.
• Occasional travel to conferences to interact with prospective users and partners, and learn where the industry is headed.

Requirements:

• Bachelors, Masters or Ph. D. in Operations Research, Industrial Engineering, Statistics, Computer Science or other quantitative/engineering fields.
• Strong understanding of analysis of algorithms, data structures and statistics.
• Solid programming experience. Including being able to quickly prototype an idea and test it out.
• Strong communication skills, including the ability and willingness to explain complicated algorithms and concepts in simple terms.
• Experience with relational databases and strong knowledge of SQL.
• Experience building data heavy analytical models in the travel industry.
• Experience in the vacation rental industry.
• Experience developing dynamic pricing models.
• Prior experience working at a fast paced environment.
• Willingness to wear many hats.

Senior Full Stack Python Engineer at Silicon Valley AI company

We at Wow Labz are always striving to look for exciting problems to solve. Whether we’re creating new products or helping a small startup extend its reach, we build from our heart. We’re entrepreneurial and we love new ideas. Fun culture with a team that cares about your development and growth.

We are looking for an expert in machine learning to help us extract maximum value from our data. You will be leading all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production. In this role, you should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research.

• Identify valuable data sources and automate collection processes
• Study and transform data science prototypes
• Research and Implement appropriate ML algorithms and tools
• Develop machine learning applications according to requirements
• Extend existing ML libraries and frameworks
• Cross-validate models to ensure their generalizability
• Present information using data visualization techniques
• Propose solutions and strategies to business challenges
• Collaborate with engineering and product development teams
• Guide and mentor the respective teams

• Proven experience as a Machine Learning Engineer or similar role
• Demonstrable history of devising and overseeing data-centered projects
• Understanding of data structures, data modeling and software architecture
• Deep knowledge of math, probability, statistics and algorithms
• Experience with cloud platforms like AWS/Azure/GCP
• Knowledge of server configurations and maintenance.
• Knowledge of R, SQL and Python; familiarity with Scala, Java or C++ is an asset
• Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)
• Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop)
• Ability to select hardware to run an ML model with the required latency
• Excellent communication skills
• Ability to work in a team
• Outstanding analytical and problem-solving skills

• Inclination towards Mathematics and statistics to understand the algorithms at a deeper level
• Strong OOPs concepts (python preferable)
• Hands on experience with Flask or Django
• Ability to learn latest deployed models and understand their core architecture to gain breadth of expertise

• You are curious and aware of the latest tech trends
• You are self-driven
• You get a kick out of leading a solution towards its completion.
• You have the capacity to foster a healthy, stimulating work environment that frequently harnesses teamwork
• You are fun to hang out with!

Job Description

We are looking for an experienced engineer to join our data science team, who will help us design, develop, and deploy machine learning models in production. You will develop robust models, prepare their deployment into production in a controlled manner, while providing appropriate means to monitor their performance and stability after deployment.

What You’ll Do will include (But not limited to):

• Preparing datasets needed to train and validate our machine learning models
• Anticipate and build solutions for problems that interrupt availability, performance, and stability in our systems, services, and products at scale.
• Defining and implementing metrics to evaluate the performance of the models, both for computing performance (such as CPU & memory usage) and for ML performance (such as precision, recall, and F1)
• Supporting the deployment of machine learning models on our infrastructure, including containerization, instrumentation, and versioning
• Supporting the whole lifecycle of our machine learning models, including gathering data for retraining, A/B testing, and redeployments
• Developing, testing, and evaluating tools for machine learning models deployment, monitoring, retraining.
• Working closely within a distributed team to analyze and apply innovative solutions over billions of documents
• Supporting solutions ranging from rule-bases, classical ML techniques  to the latest deep learning systems.
• Partnering with cross-functional team members to bring large scale data engineering solutions to production
• Communicating your approach and results to a wider audience through presentations

Your Qualifications:

• Demonstrated success with machine learning in a SaaS or Cloud environment, with hands–on knowledge of model creation and deployments in production at scale
• Good knowledge of traditional machine learning methods and neural networks
• Experience with practical machine learning modeling, especially on time-series forecasting, analysis, and causal inference.
• Experience with data mining algorithms and statistical modeling techniques for anomaly detection in time series such as clustering, classification, ARIMA, and decision trees is preferred.
• Ability to implement data import, cleansing and transformation functions at scale
• Fluency in Docker, Kubernetes
• Working knowledge of relational and dimensional data models with appropriate visualization techniques such as PCA.
• Solid English skills to effectively communicate with other team members

Due to the nature of the role, it would be nice if you have also:

• Experience with large datasets and distributed computing, especially with the Google Cloud Platform
• Fluency in at least one deep learning framework: PyTorch, TensorFlow / Keras
• Experience with No–SQL and Graph databases
• Experience working in a Colab, Jupyter, or Python notebook environment
• Some experience with monitoring, analysis, and alerting tools like New Relic, Prometheus, and the ELK stack
• Knowledge of Java, Scala or Go-Lang programming languages
• Familiarity with KubeFlow
• Experience with transformers, for example the Hugging Face libraries
• Experience with OpenCV

About Egnyte

In a content critical age, Egnyte fuels business growth by enabling content-rich business processes, while also providing organizations with visibility and control over their content assets. Egnyte’s cloud-native content services platform leverages the industry’s leading content intelligence engine to deliver a simple, secure, and vendor-neutral foundation for managing enterprise content across business applications and storage repositories. More than 16,000 customers trust Egnyte to enhance employee productivity, automate data management, and reduce file-sharing cost and complexity. Investors include Google Ventures, Kleiner Perkins, Caufield & Byers, and Goldman Sachs. For more information, visit www.egnyte.com

#LI-Remote

- Modeling complex problems, discovering insights, and identifying opportunities through the use of statistical, algorithmic, mining, and visualization techniques

- Experience working with business understanding the requirement, creating the problem statement, and building scalable and dependable Analytical solutions

- Must have hands-on and strong experience in Python

- Broad knowledge of fundamentals and state-of-the-art in NLP and machine learning

- Strong analytical & algorithm development skills

- Deep knowledge of techniques such as Linear Regression, gradient descent, Logistic Regression, Forecasting, Cluster analysis, Decision trees, Linear Optimization, Text Mining, etc

- Ability to collaborate across teams and strong interpersonal skills

Skills

- Sound theoretical knowledge in ML algorithm and their application

- Hands-on experience in statistical modeling tools such as R, Python, and SQL

- Hands-on experience in Machine learning/data science

- Strong knowledge of statistics

- Experience in advanced analytics / Statistical techniques – Regression, Decision trees, Ensemble machine learning algorithms, etc

- Experience in Natural Language Processing & Deep Learning techniques 

- Pandas, NLTK, Scikit-learn, SpaCy, Tensorflow

Responsibilities:

• Design and develop strong analytics system and predictive models
• Managing a team of data scientists, machine learning engineers, and big data specialists
• Identify valuable data sources and automate data collection processes
• Undertake pre-processing of structured and unstructured data
• Analyze large amounts of information to discover trends and patterns
• Build predictive models and machine-learning algorithms
• Combine models through ensemble modeling
• Present information using data visualization techniques
• Propose solutions and strategies to business challenges
• Collaborate with engineering and product development teams

Requirements:

• Proven experience as a seasoned Data Scientist
• Good Experience in data mining processes
• Understanding of machine learning and Knowledge of operations research is a value addition
• Strong understanding and experience in R, SQL, and Python; Knowledge base with Scala, Java, or C++ is an asset
• Experience using business intelligence tools (e. g. Tableau) and data frameworks (e. g. Hadoop)
• Strong math skills (e. g. statistics, algebra)
• Problem-solving aptitude
• Excellent communication and presentation skills
• Experience in Natural Language Processing (NLP)
• Strong competitive coding skills
• BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred

High Level Scope of Work :

• Work with AI / Analytics team to priorities MACHINE LEARNING Identified USE CASES for Development and Rollout
• Meet and understand current retail / Marketing Requirements and how AI/ML solution will address and automate the decision process.
• Develop AI/ML Programs using DATAIKU Solution & Python or open source tech with focus to deliver high Quality and accurate ML prediction Model
• Gather additional and external data sources to support the AI/ML Model as desired .
• Support the ML Model and FINE TUNEit to ensure high accuracy all the time.
• Example of use cases (Customer Segmentation , Product Recommendation, Price Optimization, Retail Customer Personalization Offers, Next Best Location for Business Est, CCTV Computer Vision, NLP and Voice Recognition Solutions)

Required technology expertise :

• Deep Knowledge & Understanding on MACHINE LEARNING ALGORITHMS (Supervised / Unsupervised Learning / Deep Learning Models)
• Hands on EXP for at least 5+ years with PYTHON and R STATISTICS PROGRAMMING Languages
• Strong Database Development knowledge using SQL and PL/SQL
• Must have EXP using Commercial Data Science Solution particularly DATAIKU and (Altryx, SAS, Azure ML, Google ML, Oracle ML is a plus)
• Strong hands on EXP with BIG DATA Solution Architecture and Optimization for AI/ML Workload.
• Data Analytics and BI Tools Hand on EXP particularly (Oracle OBIEE and Power BI)
• Have implemented and Developed at least 3 successful AI/ML Projects with tangible Business Outcomes In retail Focused Industry
• Have at least 5+ Years EXP in Retail Industry and Customer Focus Business.
• Ability to communicate with Business Owner & stakeholders to understand their current issues and provide MACHINE LEARNING Solution accordingly.

Qualifications

• Bachelor Degree or Master Degree in Data Science, Artificial Intelligent, Computer Science
• Certified as DATA SCIENTIST or MACHINE LEARNING Expert.

• Adept at Machine learning techniques and algorithms.

Feature selection, dimensionality reduction, building and

• optimizing classifiers using machine learning techniques
• Data mining using state-of-the-art methods
• Doing ad-hoc analysis and presenting results
• Proficiency in using query languages such as N1QL, SQL

Experience with data visualization tools, such as D3.js, GGplot,

• Plotly, PyPlot, etc.

Creating automated anomaly detection systems and constant tracking

• of its performance
• Strong in Python is a must.
• Strong in Data Analysis and mining is a must
• Deep Learning, Neural Network, CNN, Image Processing (Must)

Building analytic systems - data collection, cleansing and

• integration

Experience with NoSQL databases, such as Couchbase, MongoDB,

Cassandra, HBase

We are a nascent quantitative hedge fund led by an MIT PhD and Math Olympiad medallist, offering opportunities to grow with us as we build out the team. Our fund has  world class investors and big data experts as part of the GP,  top-notch ML experts as advisers to the fund, plus has equity funding to grow the team, license data and scale the data processing.

We are interested in researching and taking in live a variety of quantitative strategies based on historic and live market data, alternative datasets, social media data (both audio and video) and stock fundamental data.

You would join, and, if qualified, lead a growing team of data scientists and researchers, and be responsible for a complete lifecycle of quantitative strategy implementation and trading.

Requirements:

• Atleast 3 years of relevant ML experience
• Graduation date : 2018 and earlier
•   3-5 years of experience in high level Python programming.
• Master Degree (or Phd) in quantitative disciplines such as Statistics, Mathematics, Physics, Computer Science in top universities.
•   Good knowledge of applied and theoretical statistics, linear algebra and machine learning techniques. 
•   Ability to leverage financial and statistical insights to research, explore and harness a large collection of quantitative strategies and financial datasets in order to build strong predictive models.
• Should take ownership for the research, design, development and implementation of the strategy development and effectively communicate with other team mates
•   Prior experience and good knowledge of lifecycle and pitfalls of algorithmic strategy development and modelling. 
•   Good practical knowledge in understanding financial statements, value investing, portfolio and risk management techniques.
•   A proven ability to lead and drive innovation to solve challenges and road blocks in project completion.
• A valid Github profile with some activity in it

Bonus to have:

•   Experience in storing and retrieving data from large and complex time series databases
•   Very good practical knowledge on time-series modelling and forecasting (ARIMA, ARCH and Stochastic modelling)
•   Prior experience in optimizing and back testing quantitative strategies, doing return and risk attribution, feature/factor evaluation. 
•   Knowledge of AWS/Cloud ecosystem is an added plus (EC2s, Lambda, EKS, Sagemaker etc.) 
•   Knowledge of REST APIs and data extracting and cleaning techniques 
•   Good to have experience in Pyspark or any other big data programming/parallel computing
•   Familiarity with derivatives, knowledge in multiple asset classes along with Equities.
•   Any progress towards CFA or FRM is a bonus
• Average tenure of atleast 1.5 years in a company

• 3-5yrs of practical DS experience working with varied data sets. Working with retail banking is preferred but not necessary.
• Need to be strong in concepts of statistical modelling – particularly looking for practical knowledge learnt from work experience (should be able to give "rule of thumb" answers)
• Strong problem solving skills and the ability to articulate really well.
• Ideally, the data scientist should have interfaced with data engineering and model deployment teams to bring models / solutions to "live" in production.
• Strong working knowledge of python ML stack is very important here.
• Willing to work on diverse range of tasks in building ML related capability on the Corridor Platform as well as client work.
• Someone with strong interest in data engineering aspect of ML is highly preferred, i.e. can play dual role of Data Scientist as well as someone who can code a module on our Corridor Platform writing robust code.

Structured ML techniques for candidates:

1. GBM
2. XgBoost
3. Random Forest
4. Neural Net
5. Logistic Regression

Job Description