Discovery Research Domain Expert, IT Business Analyst

Role Summary

The Discovery Research Domain Expert will act as a vital link between scientific teams investigating causal human biology and aligning biotherapeutic modalities with disease mechanisms, utilizing Research IT data solutions. This hands-on business analyst role requires deep familiarity with early discovery Life Sciences domains, strong analytical and communication skills, and a mindset centered on translating complex scientific needs into actionable IT requirements.

This position is part of a cross-functional team that collaborates with Product Managers, Sr. Business Analysts, Data Engineers, Data Scientists, and Research stakeholders to deliver fit-for-purpose data capabilities across Biologics, Sequencing, Protein Engineering, Medicinal chemistry synthesis and evaluation, Informaticians, and more. The Discovery Research Domain Expert will play a critical role in enhancing data usability, accelerating delivery timelines, and improving stakeholder trust in our data ecosystem.

The Discovery Research Domain Expert's contributions will shape BMS's abilities to discover, develop, and deliver innovative medicines that help patients prevail over serious diseases.

Responsibilities

• Partner with Research stakeholders (Biologics, Discovery Biotherapeutics, Next Gen Sequencing, Thematic Research Centers, Chemistry, DMPK, etc.) to understand data workflows and define business requirements.
• Translate scientific needs into technical specifications, user stories, and actionable requirements for IT and engineering teams.
• Shape and prioritize demand by mapping end-to-end processes, identifying root causes of friction, and focusing on business value creation.
• Serve as the voice of the scientist, ensuring product teams deliver solutions that reflect real-world context and meet evolving needs.
• Collaborate with Data Engineers to collect, test, validate, and continuously enhance data products for usability and quality.
• Develop and maintain field-level metadata, business glossaries, and contribute to FAIR-aligned practices (Findable, Accessible, Interoperable, Reusable).
• Support scientific alignment of identifiers, terminology, and definitions across MI data sources to enhance downstream integration and analytics.
• Lead stakeholder assessments to anticipate friction, clarify expectations, and build sustained trust in data product capabilities.
• Bring an external perspective by monitoring industry trends and promoting novel approaches to data challenges.
• Communicate clearly and with influence‚Äîbridging scientific, technical, and strategic conversations across diverse audiences.
• Exhibit a growth mindset, demonstrating ownership for ongoing development in Business Analysis, AI/ML, and Pharmaceutical R&D.

Qualifications

• B.S., M.S., or Ph.D. in a relevant life sciences, informatics, or technical discipline.
• Direct experience in early life sciences domains, with explicit subject matter expertise in Molecular Invention research (e.g., Biologics, Sequencing, Protein Engineering, Antibody Discovery, Chemistry, etc.).
• Familiarity with Research workflows in pharmaceutical or biotech settings.
• 5+ years of experience in IT, informatics, or data-focused role within a scientific context.
• Proven ability to collaborate effectively across scientific and technical teams.
• Strong analytical and systems thinking skills with the ability to manage ambiguity.
• Ability to learn new tools and adapt in a dynamic environment.
• IIBA Certification or similar Business Analysis Certification, a strong plus.

Skills

• Strong commitment to a career in technology with a passion for healthcare.
• Analytical thinker with strong communication and collaboration skills, able to effectively communicate complex ideas and concepts.
• Excellent stakeholder engagement skills, with a track record of influencing without authority.
• Creative problem-solver who seeks to challenge norms and explore innovative solutions.
• Familiarity with data product development, data modeling, data mesh architecture, data governance, or analytics.

Education

• As listed in Qualifications (degree in life sciences, informatics, or technical discipline).