Data Scientist/ Associate Manager/ Manager, AI Lab

Develop, train, and fine-tune large language models for financial applications, including data analysis, report generation, and predictive modeling.

Design and implement RAG systems to integrate LLMs with internal and external financial data sources and knowledge bases.

Build and maintain robust knowledge bases containing financial data, research, and domain-specific information.

Collaborate with financial analysts and quantitative researchers to understand their needs and translate them into LLM-based solutions.

Optimize LLM performance and efficiency for financial modeling tasks.

Stay up to date with the latest advancements in LLMs, RAG, and financial technology.

Develop, test, and deploy predictive models and credit scorecards by collaborating with stakeholders, defining project scope and methodology, and processing relevant data.

Oversee the project lifecycle, engaging with internal teams to ensure timely delivery of high-quality results and maintaining comprehensive documentation.

Implement software development best practices, including version control, testing, and code reviews.

Post Graduation/Graduation from a UGC-approved university with a satisfactory academic track record preferably in Computer Science / Software Engineering /Data Science / Artificial Intelligence / Machine Learning /Statistics / Applied Mathematics or Electrical & Computer Engineering.

Minimum 1 year of hands-on experience in Large Language Models (LLMs), NLP, or building Agentic AI workflows is preferred

Proficient in building RAG systems, knowledge bases, vector databases

Credit risk modeling, scorecard development, or predictive modeling will be an added advantage

Expertise in working with cloud platforms or GPU-based model training

· Strong analytical and problem-solving skills.

Proficient in customer centricity, self-propelled, and capable of meeting deadlines