Senior Manager, Research Intelligence Engineer

Bristol Myers Squibb

. Partner with scientists, portfolio teams, product owners, and operations leaders to frame complex business and scientific questions as actionable intelligence opportunities .

Posted 10/9/2026full-timeUnited StatesSenior💰 $134,980 - $179,920 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and delivering AI-enabled workflows and data solutions, with a strong foundation in software and data engineering, particularly in Python, SQL, and cloud data platforms. Capable of translating complex scientific and business needs into actionable intelligence and measurable outcomes while ensuring adherence to FAIR principles and responsible AI practices.

Highest-signal resume keywords

Generative AI ExperienceData Engineering SkillsPython ProgrammingDatabricks ProficiencyRequirements Analysis

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringSoftware DevelopmentGenerative AIAPIsSQLCI/CD PracticesCloud Data PlatformsProcess MappingTechnical DocumentationData Quality

Soft Skills

Communication SkillsFacilitation SkillsSystems ThinkingMentoring SkillsCuriosity

Tools & Technologies

DatabricksCloud-Native ArchitectureKnowledge GraphsSemantic ModelsModel Evaluation FrameworksEnterprise AI Platforms

Industry Keywords

Pharmaceutical R&DDrug DiscoveryResearch Portfolio OperationsMolecular InventionFAIR Principles

Tech Stack

Tools & technologies

CloudPythonSQL

About the role

Key responsibilities & impact

Partner with scientists, portfolio teams, product owners, and operations leaders to frame complex business and scientific questions as actionable intelligence opportunities
Develop 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
Analyze complex, unscoped Research data, workflow, and operational problems and identify opportunities for data, automation, or agentic capabilities
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
Build AI-enabled workflows combining 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
Engineer and integrate data services, semantic context, metadata, APIs, and platform components
Work with Databricks, ResearchCentral, Research data products, source systems, and enterprise tooling to deliver secure end-to-end solutions
Apply modular design, version control, automated testing, CI/CD, monitoring, and production support
Partner with architecture, engineering, platform, security, and governance teams on enterprise standards and FAIR data principles
Own value workstreams from discovery and architecture through delivery, validation, release, adoption, and operational support
Develop roadmaps and delivery plans; define success measures and improve solutions using adoption, quality, cycle time, feedback, and decision-impact evidence
Identify risks, dependencies, data gaps, and process gaps and coordinate resolution across teams
Support change, documentation, training, and adoption
Provide technical partnership, design guidance, code and solution reviews, troubleshooting, mentorship, and investment recommendations
Build a community of practice for Research Intelligence and agentic engineering
Champion standards for AI orchestration, evaluation, governance, observability, Process Context Mapping, capability reuse, controls, and traceability

Requirements

What you’ll need

Bachelor’s degree in computer science, engineering, data science, life sciences, or a related discipline
6+ years of relevant experience designing and delivering production data, software, or analytics solutions in a complex enterprise environment
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
Familiarity with portfolio planning, asset progression, scientific and operational metrics, and Research decision-makers’ information needs
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
Experience moving capabilities from prototype through production, adoption, and measurable value realization
Curiosity, pragmatism, and ability to learn new Research domains quickly while maintaining engineering discipline

Benefits

Comp & perks

Discretionary incentive cash and stock opportunities
Wellbeing support
Retirement and financial protection benefits
Medical, dental, vision, life and disability insurance
Flexible Time Off (FTO) without a set accrual limit for eligible U.S.-based exempt employees
11 paid company holidays annually
160 hours of paid vacation annually for eligible new hires
3 optional holidays for eligible non-exempt, RayzeBio, and Puerto Rico employees
Paid sick leave
Up to two paid volunteer days per year
Summer hours flexibility
Medical, personal, parental, caregiver, bereavement, and military leaves of absence
Annual Global Shutdown between Christmas Day and New Year's Day for eligible employees
Workplace accommodations/adjustments and ongoing support for people with disabilities