Overview
Data Scientist III role at Bristol Myers Squibb focused on designing and deploying advanced data science and AI solutions, including machine learning and LLM-based applications, on large clinical and healthcare datasets.
What you'll do
- Collaborate with business to design, develop, and deploy advanced data science and AI solutions leveraging machine learning, large language models (LLMs), and modern data platforms.
- Work with large-scale structured and unstructured datasets including clinical data, publications, real-world evidence, and other healthcare datasets.
- Build predictive models and advanced analytics solutions to generate actionable insights and support data-driven decision making.
- Develop LLM-powered applications such as AI assistants, knowledge-grounded reasoning systems, and Retrieval-Augmented Generation (RAG) pipelines.
- Develop and maintain semantic layers, ontologies, and contextual data frameworks that enable consistent interpretation of data across AI systems and analytics workflows.
- Implement evaluation frameworks for AI systems, response quality assessment, hallucination mitigation, and benchmark-driven validation.
- Partner with data engineering and platform teams to ensure scalable pipelines, high-quality data availability, and production-ready AI systems.
- Communicate analytical findings and AI-driven insights clearly to both technical and non-technical stakeholders through reports, visualizations, and presentations.
- Mentor junior data scientists and contribute to knowledge sharing and adoption of modern AI development practices.
What you'll need
- Strong expertise in machine learning and predictive modeling techniques.
- Strong programming proficiency in Python for data science and AI system development.
- Experience working with modern data platforms such as Databricks (Spark, MLflow, Delta Lake).
- Experience building LLM-based applications, including Retrieval-Augmented Generation (RAG), AI copilots, and knowledge-grounded AI systems.
- Experience implementing embedding pipelines and vector database architectures (e.g., FAISS, Pinecone, Weaviate, OpenSearch Vector, pgvector).
- Familiarity with agentic AI frameworks such as LangGraph, LangChain, CrewAI, or similar orchestration frameworks.
- Experience designing multi-step AI workflows, including tool calling, context management, and agent-to-agent interaction.
- Understanding of LLMOps practices, including model deployment, monitoring, prompt engineering, evaluation workflows, and experiment tracking.
- Experience developing and deploying AI or ML services using FastAPI or similar frameworks for scalable APIs.
- Experience with semantic data modelling, ontologies, and contextual data frameworks to enable AI reasoning across complex datasets.
- Proficiency in working with large datasets using SQL and distributed data processing frameworks.
- Excellent communication and presentation skills to convey complex technical concepts to both technical and non-technical audiences.
- Btech/Masters in a relevant field such as Data Science, Statistics, Computer Science or a related discipline.
- 5+ years of experience in data science, machine learning, or applied AI roles.
- Proven experience building and deploying machine learning or LLM-powered systems in production environments.
- Experience working with large-scale structured and unstructured datasets.
- Experience developing AI-powered decision support tools, or knowledge-based systems.
Nice to have
- Experience applying data science or AI techniques in healthcare, life sciences, or biopharma domains.
- Familiarity with clinical data, healthcare datasets, or real-world evidence sources.
- Understanding of the pharma ecosystem and healthcare data sources.
Details
- Location: Hyderabad, Telangana, India.
- Work model is assigned based on core responsibilities (site-essential, site-by-design, field-based or remote-by-design).
Read the full description and apply on the company’s own careers page.