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Lead Analytics/Architect (Generative AI) at Infogain

About Infogain

Infogain is a human-centered digital platform and software engineering company based out of Silicon Valley. We engineer business outcomes for Fortune 500 companies and digital natives in the technology, healthcare, insurance, travel, telecom, and retail & CPG industries using technologies such as cloud, microservices, automation, IoT, and artificial intelligence. We accelerate experience-led transformation in the delivery of digital platforms. Infogain is also a Microsoft (NASDAQ: MSFT) Gold Partner and Azure Expert Managed Services Provider (MSP).

Infogain, an Apax Funds portfolio company, has offices in California, Washington, Texas, the UK, the UAE, and Singapore, with delivery centers in Seattle, Houston, Austin, Kraków, Noida, Gurgaon, Mumbai, Pune, and Bengaluru.

Infogain is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Want to know more? Log on to - www.infogain.com

About the Team

At Infogain, the Data & AI Studio team is at the forefront of AI/ML innovation. We have developed NAVIK AI, a suite of AI/ML-powered solutions designed for marketing and sales domains. This suite includes flagship products such as ASK NAVIK, NAVIK MarketingAI, and NAVIK SalesAI. Our ambitious goal is to continue enhancing these products and expand the suite further.

Our team blends Data, Analytics, and Technology to deliver impactful business results. We are looking to add a Junior Data Scientist specializing in Generative AI to support the ongoing evolution and development of our NAVIK AI suite.

Job Summary

Infogain is seeking a motivated and innovative Junior Data Scientist 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 assist in enhancing the analytics backend of our flagship products and contribute to advancing our knowledge discovery solutions. This role is perfect for someone who enjoys learning, creative problem-solving, and working in a dynamic environment.

Eligibility

Minimum Qualifications:

· Bachelor’s degree in computer science or a related field OR master’s degree in statistics, economics, business economics, econometrics, or operations research.

· 7-10 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.

— Ensure alignment of analytical plans with the customer’s 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