Data Scientist - Generative AI (12-15 yrs)

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, Krakw, 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.

Job Summary :

Infogain is seeking a motivated and innovative 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.