Senior Manager, AI-Driven Research Intelligence

Bristol-Myers Squibb Co; Princeton (NJ); On-site; USD 150,000 - 200,000; Full time

Job summary

Bristol Myers Squibb in Princeton, NJ is seeking a Senior Manager to advance Research Intelligence & data capabilities within Molecular Invention Data | R&D Data & Analytical Platforms BI&T. You will lead AI-enabled, data-driven workflows and guide solution design across researchers and product teams.

Ideal candidates have hands-on experience with generative AI, strong software engineering fundamentals, and the ability to deliver end-to-end solutions in a complex enterprise environment.

Qualifications

• Bachelor’s degree in computer science, engineering, data science, life sciences, or a related discipline; advanced degree or equivalent experience preferred.
• 6+ years of relevant experience designing and delivering production data, software, or analytics solutions in a complex enterprise environment.
• Demonstrated hands-on experience with generative AI or agentic systems, including orchestration, retrieval, tools or APIs, evaluation, observability, and responsible AI controls.
• Strong software and data engineering foundation, including Python or a comparable language, SQL, APIs, cloud data platforms, source control, testing, and CI/CD practices.
• Experience eliciting requirements, analyzing processes and data, and translating domain needs into implementable technical designs.
• Ability to establish credibility with scientific and technical stakeholders, navigate ambiguity, and lead complex work across organizational boundaries.
• Excellent written and verbal communication, facilitation, systems-thinking, and technical mentoring skills.

Responsibilities

• Frame ambiguous business and scientific questions as actionable intelligence opportunities.
• Lead discovery, requirements analysis, process decomposition, and Process Context Mapping for AI-enabled and data-driven workflows.
• Take the lead in analyzing significantly complex, unscoped Research data, workflow, and operational problems; identify business opportunities and areas of operational whitespace where data, automation, or agentic capabilities can create measurable value.
• Translate domain needs into prioritized use cases, product requirements, data requirements, acceptance criteria, and measurable outcomes.
• Design, prototype, engineer, and productionize agentic and generative AI capabilities that support Research portfolio management, operational excellence, and scientific decision-making.
• Build AI-enabled workflows that combine enterprise data, domain context, retrieval, tools, APIs, models, and human decision points.
• Implement evaluation, testing, observability, guardrails, and feedback mechanisms for reliable and responsible AI behavior.
• Create reusable patterns, components, and technical documentation that accelerate adoption across Research tools and data.
• Engineer and integrate the data services, semantic context, metadata, APIs, and platform components required for Research Intelligence solutions.
• Develop strong hands-on expertise in Databricks as the organization’s data intelligence platform, and work across ResearchCentral, Research data products, source systems, and enterprise tooling to deliver secure, maintainable end-to-end solutions.
• Apply sound software and data engineering practices, including modular design, version control, automated testing, CI/CD, monitoring, and production support.
• Partner with data architecture, data engineering, platform, security, and governance teams to align solutions with enterprise standards and FAIR data principles.
• Own value workstreams from discovery and architecture through iterative delivery, validation, release, adoption, and operational support.
• Develop roadmaps and delivery plans that balance near-term experimentation with scalable, supportable enterprise capability.
• Define success measures and use evidence from adoption, quality, cycle time, user feedback, and decision impact to improve solutions.
• Identify delivery risks, dependencies, and data or process gaps early, and coordinate resolution across teams.
• Support change, documentation, training, and adoption so that technical capabilities become sustained Research practices.
• Serve as a technical partner to Research leaders, product owners, domain experts, architects, engineers, data scientists, and external delivery teams.
• Communicate complex domain and technical concepts clearly across scientific, product, engineering, and leadership audiences.
• Provide design guidance, code and solution reviews, troubleshooting support, and technical mentorship to engineers and analysts.
• Contribute to investment recommendations by clarifying expected value, feasibility, data readiness, delivery effort, and operational risk.
• Help build a community of practice for Research Intelligence and agentic engineering across Research, BI&T, and R&D Data ecosystem.

Skills

Generative AI / agentic systems

Python & SQL

Data engineering fundamentals

Communication & stakeholder management

Cloud data platforms

Education

Bachelor’s degree in computer science, engineering, data science, life sciences, or related

Advanced degree preferred

Tools

Databricks

Git

CI/CD

Job description

Bristol Myers Squibb in Princeton, NJ is seeking a Senior Manager to advance Research Intelligence & data capabilities within Molecular Invention Data | R&D Data & Analytical Platforms BI&T. You will lead AI-enabled, data-driven workflows and guide solution design across researchers and product teams.

Ideal candidates have hands-on experience with generative AI, strong software engineering fundamentals, and the ability to deliver end-to-end solutions in a complex enterprise environment.