Senior Data Scientist
Bristol Myers Squibb
5 hours ago
Remote friendly (Seattle, WA)
United States
IT
Summary / Role
- Convert ambiguous scientific/business opportunities into measurable AI product hypotheses, experiments, and working solutions across R&D, Commercialization, Manufacturing, and Enabling.
- Design evaluation datasets; build analytical features; prototype models; test agent/retrieval performance; measure product impact; and explain model behavior.
Key Responsibilities
- Frame questions into hypotheses, success metrics, evaluation plans, and rapid experiments.
- Build prototypes (Python, SQL, notebooks, APIs, AWS-aligned services) and support sandboxed, non-production data experimentation.
- Curate/evaluate “analytical context” for agents (instructions, memory, tools, warehouse context, curated source meaning); develop embeddings/classifiers/ranking and recommendation/optimization methods.
- Design/evaluate LLM/RAG/agentic workflows using rubrics, golden datasets, structured validation, error taxonomies, hallucination risk measurement, and SME loops (e.g., LangGraph/LangSmith).
- Define KPIs and analytical measurement plans; apply experimental design/causal inference; produce analyses/visualizations/narratives; partner on privacy, integrity, and governance.
Qualifications & Required/Preferred Skills
- BS+ in Data Science/Stats/CS/Engineering/Bioinformatics/Computational Biology/Applied Math or related.
- 5+ years in data science/ML/applied AI/analytics.
- Python, SQL, and common DS/ML libraries (e.g., pandas, NumPy, scikit-learn, PyTorch/TensorFlow, statsmodels).
- Experience with LLMs, RAG, agentic AI, evaluation design, structured outputs, and context/knowledge curation.
- AWS familiarity (S3, Athena, RDS/PostgreSQL, OpenSearch, SageMaker/Bedrock or equivalents) and vector DBs/knowledge graphs/embeddings.
- Experience communicating findings to technical and non-technical audiences; effective use of AI coding tools.
Compensation & Benefits (as stated)
- Compensation range: $137,530–$183,319 (location-dependent). Benefits include health coverage, wellbeing programs, 401(k) and insurance; paid time off (flexible or vacation/holiday structure by location).
Application Instructions
- If the role isn’t a perfect resume match, apply anyway.
- Convert ambiguous scientific/business opportunities into measurable AI product hypotheses, experiments, and working solutions across R&D, Commercialization, Manufacturing, and Enabling.
- Design evaluation datasets; build analytical features; prototype models; test agent/retrieval performance; measure product impact; and explain model behavior.
Key Responsibilities
- Frame questions into hypotheses, success metrics, evaluation plans, and rapid experiments.
- Build prototypes (Python, SQL, notebooks, APIs, AWS-aligned services) and support sandboxed, non-production data experimentation.
- Curate/evaluate “analytical context” for agents (instructions, memory, tools, warehouse context, curated source meaning); develop embeddings/classifiers/ranking and recommendation/optimization methods.
- Design/evaluate LLM/RAG/agentic workflows using rubrics, golden datasets, structured validation, error taxonomies, hallucination risk measurement, and SME loops (e.g., LangGraph/LangSmith).
- Define KPIs and analytical measurement plans; apply experimental design/causal inference; produce analyses/visualizations/narratives; partner on privacy, integrity, and governance.
Qualifications & Required/Preferred Skills
- BS+ in Data Science/Stats/CS/Engineering/Bioinformatics/Computational Biology/Applied Math or related.
- 5+ years in data science/ML/applied AI/analytics.
- Python, SQL, and common DS/ML libraries (e.g., pandas, NumPy, scikit-learn, PyTorch/TensorFlow, statsmodels).
- Experience with LLMs, RAG, agentic AI, evaluation design, structured outputs, and context/knowledge curation.
- AWS familiarity (S3, Athena, RDS/PostgreSQL, OpenSearch, SageMaker/Bedrock or equivalents) and vector DBs/knowledge graphs/embeddings.
- Experience communicating findings to technical and non-technical audiences; effective use of AI coding tools.
Compensation & Benefits (as stated)
- Compensation range: $137,530–$183,319 (location-dependent). Benefits include health coverage, wellbeing programs, 401(k) and insurance; paid time off (flexible or vacation/holiday structure by location).
Application Instructions
- If the role isn’t a perfect resume match, apply anyway.