Senior Data Scientist - Genai

As a Senior GenAI Data Scientist, you will partner closely with a team of stake holders, product managers, and data engineers to solve real problems in healthcare domain, with particular focus on GenAI LLM with RAG / knowledge base and reinforcement learning / fine-tuning.

We are looking for great problem solvers who can tap into the potential of data and deliver scalable and robust data products. Our potential member would work on developing and implementing generative AI and machine learning algorithms for various Products and Solutions

Job Responsibilities

• Leverage GenAI techniques and solutions to solve healthcare problems.
• Understand solution requirements: input, output, ground truth, accuracy/evaluation metric, speed, etc.
• Inventory publically available data sets and/or acquire in-house data sets.
• Develop data pipelines to acquire, cleanse, and prepare healthcare data for AI.
• Study state of the art and other competitive exisiting solutions and select canditates for benchmarks and integration. Identify and communicate opportunities for potential improvements above SOTA.
• Run statistical evaluations and perform sensitivity analysis. Communicate findings in reports and presentations.
• Containerize solution and document solution for sharing with team.
• Lead company efforts toward GenAI knowledge base RAG and reinforcement learning .

Desired profile

• PhD / Master’s degree (+ 1-3 years professional experience) / Bachelor’s (+ 3-5 years professional experience) in computer science, Mathematics, Statistics, Physics, Electrical Engineering, Computer Engineering or related fields from tier 1 college
• Have 3 - 5 years of experience in analyzing large volumes of data and building predictive models.
• Strong hands-on knowledge of python, pytorch, huggingface, pandas, numpy, pyplot, scikit-learn.
• Strong experience in Agentic AI e.g. langchain, langgraph, deep_agents, with a strong focus on LLMs and Gen AI based modelling.
• Strong experience in knowledge base / RAG techniques.
• Strong experience in LLM reinforcement learning / fine-tuning and relevant libraries e.g. TRL, unsloth, deepspeed.
• Understands the core concepts of AI tools and technologies, general best practices, and the math behind it. Proficient in git, docker.
• Ability to work closely with Domain experts to develop tools/algorithms needed to answer research questions in their studies.
• Excellent Communication Skills (with the ability to explain developed tools and ML algorithms to a non-technical audience)
• Ability to formulate operational problems in healthcare domain as technical problems that allows for reuse of leading research in the area.
• Proven ability to work independently to learn new technologies, techniques, processes, languages, platforms, systems.
• Strong analytical, inferential, critical thinking, and creative problem-solving skills. ability to work both independently and with a team.

Preferred Qualifications:

• Expert in Agentic AI + knowledge base / RAG + LLM reinforcment learning / fine-tuning.
• Expert software development skills including developing and maintaining good production quality code.