Data Scientist III

Bristol Myers Squibb
Washington, DC, United States
5 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

LangGraph Framework Artificial Intelligence Big Data Clinical Data Repository Encodings Computer Programming Databases Information Engineering Data Infrastructure Decision Support Systems Distributed Computing Environment Knowledge-Based Systems
+29 more
Machine Learning Azure Machine Learning SQL Databases Unstructured Data Pinecone LangChain System Availability Large Language Models Prompt Engineering Apache Spark Hallucination Detection Generative AI Agentic-AI Fastapi Pgvector Data Lakes Kubernetes Information Technology CrewAI Data Analytics Weaviate Integration Frameworks Machine Learning Operations FAISS Restful APIs Automation Anywhere OpenSearch AI Co-pilot Databricks

Job description

  • 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., Where you work matters - because collaboration, innovation and patient impact happen in many settings. Our roles are structured across four work models site-essential, site-by-design, field-based and remote-by-design. The model assigned to this role is based on its core responsibilities. Learn more at https //careers.bms.com/ways-of-working.

Supporting People With Disabilities

BMS is dedicated to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace accommodations/adjustments and ongoing support in their roles. Applicants can request a reasonable workplace accommodation/adjustment prior to accepting a job offer. If you require reasonable accommodations/adjustments in completing this application, or in any part of the recruitment process, direct your inquiries to adastaffingsupport@bms.com. Visit careers.bms.com/eeo-accessibility to access our complete Equal Employment Opportunity statement.

Candidate Rights

BMS will consider qualified applicants with arrest and conviction records, pursuant to applicable laws in your area.

Requirements

  • 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 fields 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.
  • Experience applying data science or AI techniques in healthcare, life sciences, or biopharma domains is highly desirable.
  • Familiarity with clinical data, healthcare datasets, or real-world evidence sources is a plus.
  • Understanding of the pharma ecosystem and healthcare data sources is beneficial.

About the company

At Bristol Myers Squibb, our employees often ask, β€œWho are you working for?”-a question that fuels collaboration, accountability, and urgency in our work. Our purpose-driven culture inspires us to discover, develop, and deliver innovative medicines to prevail over serious diseases. We offer uniquely interesting and meaningful work, opportunities for growth, and a supportive environment that values inclusion, wellbeing, flexibility, and comprehensive benefits. This is work that transforms the lives of patients, and the careers of those who do it.

Roles And Responsibilities

  • 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.

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