Jobs at Bristol Myers Squibb

Leads clinical data management across multiple pharmaceutical and biotech clinical trials. Oversees data management personnel, CROs, vendors, timelines, quality, data integrity, clinical systems, and regulatory compliance. Reviews data listings and visualizations for quality and trend analysis, manages third-party laboratory data interactions, participates in cross-functional meetings, and contributes to SOP development. Requires at least six years of data management experience and may require 10% travel.

Provides strategic and operational leadership for global clinical trials, overseeing study teams, CROs, vendors, budgets, timelines, quality, risk mitigation, and regulatory compliance. Leads trial planning, execution, closeout, inspection readiness, and cross-functional decision-making. Contributes to clinical development plans and protocol design, drives process improvements, and supports governance activities. The role requires pharmaceutical or biotech clinical operations experience, including oncology trials, with up to 20% travel.

Leads Phase I–III clinical trial planning, execution, and closeout. Oversees CROs, vendors, budgets, timelines, site activation, enrollment, data quality, risk mitigation, and regulatory compliance. Coordinates cross-functional study teams, monitors performance, escalates issues, and supports operational strategy. Requires 5–7 years of clinical operations experience in biotech, pharma, or CRO settings, with up to 20% travel.

Lead and execute non-interventional retrospective oncology research using large datasets; develop protocols, perform statistical programming and analyses, communicate results to stakeholders, provide methodological leadership, mentor staff, and collaborate with HEOR, medical, and market access teams to support value-focused outcomes research.

Lead biostatistician for oncology clinical trials: design statistical strategies, author SAPs and TLFs, validate vendor deliverables, collaborate cross-functionally, support regulatory submissions, pilot AI initiatives, and provide strategic statistical guidance throughout drug development. Travel ~10%.

Lead design, prototyping, and scaling of LLM-enabled AI capabilities for drug discovery research. Partner with scientists and engineers to build agentic systems, evaluation frameworks, grounding and provenance infrastructure, and reusable AI building blocks that improve research decision-making and scientific quality.