Associate Data Scientist - Value and Access Strategy

Overview

Associate Data Scientist role within the US Value & Access organization, building and deploying AI-powered platforms for commercial, contracting, and patient access strategies, from prototype to production.

What you'll do

• Build LLM-powered assistants, implement prompt engineering, Retrieval-Augmented Generation (RAG) pipelines, and agentic workflows and related applications
• Extract, classify, and query insights from unstructured documents (contracts, policies, SOPs); build NLP pipelines for semantic search and summarization
• Work on data ingestion, transformation, and feature engineering pipelines; contribute to scalable AI/ML infrastructure
• Build APIs, dashboards, and backend services that power AI-driven insights for end users
• Develop anomaly detection models (e.g., claims, pricing, Gross-to-Net); build forecasting and optimization models to support commercial decisions
• Collaborate with cross-functional technical teams to translate business needs into technical specifications, focusing on AI-driven automation and insights
• Participate in code reviews, design discussions, and adopt best practices across MLOps and software engineering

What you'll need

• Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, Statistics, Engineering, or other STEM majors
• 2–6 years of hands-on experience in AI/ML, data science, or software engineering roles
• Demonstrated portfolio of AI/ML projects (GitHub, publications, or production deployments)
• Mandatory hands-on experience with 2–3 real AI/ML projects, such as an LLM-based chatbot with RAG (document Q&A), AI summarization tools, or agent-based multi-step reasoning systems, and deployed ML models (API or web app) or data pipelines (ETL/ELT)
• Strong programming skills in Python, PySpark, and SQL
• Solid understanding of Data Structures & Algorithms, OOP, and System Design fundamentals
• Hands-on experience with core Machine Learning techniques (Regression, Classification, Clustering)
• Working knowledge of NLP fundamentals (tokenization, embeddings, transformers)
• Exposure to LLMs (OpenAI, HuggingFace, Anthropic, etc.) and prompt engineering / GenAI workflows
• Experience with data manipulation libraries (Pandas, NumPy) and working with both structured and unstructured data
• Familiarity with REST APIs and backend development basics
• Initiative to explore new technologies and alternate approaches to solving problems
• Strong analytical and troubleshooting skills with the ability to break down complex problems
• Excellent verbal and written communication skills
• Ability to work effectively with global, virtual, cross-functional teams
• High degree of curiosity, initiative, and self-motivation
• Team-oriented mindset with a focus on collective goals
• Ability to manage multiple priorities and learn quickly in a fast-paced environment

Nice to have

• Experience with RAG pipelines and vector databases (FAISS, Pinecone, Chroma, Weaviate)
• Hands-on experience with LangChain, LlamaIndex, or agent frameworks (AutoGen, CrewAI)
• Exposure to MLOps tools (Docker, CI/CD, MLflow, Kubeflow, Airflow)
• Knowledge of time-series forecasting and anomaly detection techniques
• Frontend basics (Streamlit, React) for building dashboards and demos
• Familiarity with cloud platforms (AWS, Azure, or GCP)
• Experience with Databricks for data analytics and ML workflows
• Foundational understanding of the US pharmaceutical ecosystem, relevant datasets (e.g., claims, prescription data), and Patient Support Services offerings
• Any AWS / Azure / GCP certification
• Any Python, Machine Learning, or GenAI certification

Details

• Location: Hyderabad, India