Data Scientist

Job Description:

Job Summary

We are seeking a motivated and innovative senior developer with a specialization in Generative AI. The ideal candidate will be enthusiastic about exploring new problems, driving innovation, and leveraging advanced machine learning techniques and programming skills (especially in Python). You will work on real-life client problems building production-grade AI / GenAI solutions. This role is perfect for someone who enjoys learning, creative problem-solving, and working in a dynamic environment.

Eligibility

Minimum Qualifications:

Bachelors degree in computer science or a related field OR masters degree in statistics, economics, business economics, econometrics, or operations research.

12-15 years of experience in the Analytics/Data Science domain.

Proficiency in programming languages such as Python.

Experience with Generative AI techniques and tools.

Familiarity with ETL methods, data imputation, data cleaning, and outlier handling.

Familiarity with cloud platforms (AWS, Azure, GCP) and AI/ML services.

Knowledge of databases and associated tools such as SQL.

Technical Skills Desirable:

Expertise in NLP and Generative AI concepts/methods/techniques like

Prompt design/engineering

Retrieval Augmented Generation (RAG), Corrective RAG and Knowledge Graph-based RAG using GPT-4o

Fine-tuning through LORA/QLORA

Multi-agentic frameworks for RAG

Reranker etc. for enhancing the plain-vanilla RAG

Evaluation frameworks like G-Eval etc.

Strong understanding of Deep Learning methods and Machine Learning techniques including Ensemble methods, Support Vector Machines, and Natural Language Processing (NLP).

Exposure to Big Data technologies like Hadoop, Hive, Spark.

Experience with advanced reporting tools such as Tableau, Qlikview, or PowerBI.

Specific Responsibilities

Requirement Gathering:

Translate business requirements into actionable analytical plans in collaboration with the team and business analyst.

Ensure alignment of analytical plans with the customers strategic objectives.

Data Handling:

Identify and leverage appropriate data sources to address business problems.

Explore, diagnose, and resolve data discrepancies, including ETL tasks, missing values, and outliers.

Project Leadership and Execution:

Individually lead projects, proof-of-concept (POC) initiatives, or development efforts from inception to completion.

Contribute to the development and refinement of technical and analytics architecture, ensuring it aligns with project and organizational goals.

Design and implement scalable and robust analytical frameworks and data pipelines to support advanced analytics and machine learning applications.

Manage project timelines, resources, and deliverables, coordinating with cross-functional teams to achieve project goals.

Ensure the delivery of production-ready models and solutions, meeting quality and performance standards.

Monitor success metrics to ensure high-quality output and make necessary adjustments.

Create and maintain documentation/reports.

Mentoring and Team Development:

Mentor junior data scientists, providing guidance on technical challenges and career development.

Facilitate knowledge sharing within the team, promoting best practices and fostering a collaborative environment.

Conduct code reviews to ensure high-quality, maintainable, and efficient code.

Innovation and Best Practices:

Stay informed about new trends in Generative AI and integrate relevant advancements into our solutions.

Implement novel applications of Generative AI algorithms and techniques in Python.

Evaluate and adopt best practices in AI/ML development to enhance the effectiveness and efficiency of our solutions.

Sample Projects

GenAI-powered self-serve analytics solution for a global technology giant, that leverages the power of multi-agent framework and Azure OpenAI services to provide actionable insights, recommendations, and answers to tactical questions derived from web analytics data.

GenAI bot for querying on textual documents (e.g., retail audit orientation, FAQ documents, research brief document etc.) of multinational dairy company and, and getting personalized responses in a natural and conversational way, based on the structured context of the user (like their personal details), along with the citations, so that one can effortlessly carry out their first-hand validation themselves

GenAI bot for querying on tabular dataset (like monthly KPI data) of leading global event agency to understand, process natural language queries on the data and generate appropriate responses in textual, tabular and visual formats.

GenAI-powered advanced information retrieval from structured data of a global technology leading organization

TimesFM modelling for advanced time series forecasting for a global retail chain

Knowledge-Graph-based GenAI solution for knowledge retrieval and semantic summarization for a leading global event agency

GenAI-powered shopping assistant solution for big-box warehouse club retail stores

GenAI solution using multi-agentic framework for travel-hospitality use case

Input Governance and Response Governance in GenAI Solutions

Development and implementation of evaluation frameworks for GenAI solutions/applications

Training Foundational Models on new data using open-source LLM or SLM