Senior Manager, Research Intelligence Engineer
Bristol-Myers Squibb Co
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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
Education
Tools
Job description
At Bristol Myers Squibb, our employees often ask, “Who 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.
Bristol Myers Squibb seeks a hands-on, technically accomplished Senior Manager to advance Research Intelligence & data capabilities within Molecular Invention Data | R&D Data & Analytical Platforms BI&T.
- Partner with scientists, portfolio teams, product owners, and operations leaders to frame ambiguous business and scientific questions as actionable intelligence opportunities.
- Develop sufficient understanding of Research domains, portfolio processes, decision points, data semantics, and user needs to guide solution design.
- 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 rather than waiting for opportunities to be predefined.
- 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.
- Adopt, apply, and champion standards for AI orchestration, evaluation, governance, observability, Process Context Mapping, and capability reuse.
- Ensure that sensitive Research data, model outputs, tool access, and human approvals are handled through appropriate controls and traceability.
- Promote common patterns for contextual intelligence, knowledge retrieval, workflow orchestration, and integration rather than isolated point solutions.
- Capture lessons, reference architectures, and reusable assets that improve delivery speed and reduce technical and institutional knowledge risk.
- 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.
- Experience in pharmaceutical R&D, drug discovery, molecular invention, research portfolio operations, or an adjacent scientific domain.
- 6+ years of relevant experience designing and delivering production data, software, or analytics solutions in a complex enterprise environment.
- Familiarity with portfolio planning, asset progression, scientific and operational metrics, and the information needs of Research decision makers.
- Experience with Databricks, cloud-native architecture, knowledge graphs or semantic models, vector retrieval, model evaluation frameworks, and enterprise AI platforms.
- Experience with data products, metadata, data quality, lineage, governance, and FAIR principles.
- Product-oriented mindset with experience moving capabilities from prototype through production, adoption, and measurable value realization.
- Curiosity, pragmatism, and the ability to learn new Research domains quickly while maintaining strong engineering discipline.
- Brisbane - CA - US: $148,480 - $179,920
- Cambridge Crossing: $148,480 - $179,920
- Princeton - NJ - US: $134,980 - $163,564
- San Diego - CA - US: $148,480 - $179,920
- Tampa - FL - US: $134,980 - $163,564
The starting pay range(s) listed above is for full-time employees (FTE). You may also be eligible for additional discretionary incentive cash and stock opportunities. We determine starting pay thoughtfully – carefully considering the nature of the role, required skills, work location, schedule and the knowledge and experience you bring. Final compensation is guided by pay equity principles and applicable employment laws. Compensation programs are reviewed on an ongoing basis and may be adjusted over time to reflect evolving market factors, and individual, team or Company performance.
- Subject to the terms and conditions of the applicable plans then in effect, you may be eligible to participate in our comprehensive benefit plans – including wellbeing support, retirement and financial protection benefits, and insurance offerings (medical, dental, vision, life and disability).
- U.S.-based exempt employees are eligible for Flexible Time Off (FTO), which provides paid time off without a set accrual limit, subject to manager approval, along with 11 paid company holidays each year.
- Non-exempt employees, RayzeBio employees, and employees located in Puerto Rico receive 160 hours of paid vacation annually for new hires (subject to manager approval), 11 paid company holidays, and 3 optional holidays.
- Depending on eligibility, employees may also have access to additional time-off benefits, including paid sick leave, up to two paid volunteer days per year, summer hours flexibility, and leaves of absence for medical, personal, parental, caregiver, bereavement, or military needs.
- Eligible employees also enjoy an annual Global Shutdown between Christmas Day and New Year's Day.
- U.S.-based job seekers can explore full benefit offerings at https://careers.bms.com/benefits
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.
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.
BMS will consider qualified applicants with arrest and conviction records, pursuant to applicable laws in your area. For roles based in Los Angeles County only: If you live in or expect to work from Los Angeles County if hired for this position, please visit this page for important additional information: https://careers.bms.com/california-residents/
We will never request payments, financial information, or social security numbers during our application or recruitment process. Learn more about protecting yourself at https://careers.bms.com/fraud-protection. Any data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations. If this posting is missing required information required by local law or incorrect, contact BMS at TAEnablement@bms.comwith the Job Title and Requisition number. Do not send application-related inquiries to this email. To check your application status, please login to your Candidate Home Account.
R1607271 : Senior Manager, Research Intelligence Engineer Data Privacy Link
We’re creating innovative medicines for patients fighting serious diseases. We’re also nurturing our own diverse team with inspiring work and challenging career options. No matter the role, each one of us makes a contribution. And that makes all the difference.
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