Role Overview
Experienced BA needed to join Cognizant's Life Sciences R&D platform delivery team. You will bridge PhD-level scientific stakeholders and engineering teams — translating omics, biomarker, and molecular research workflows into clear, testable requirements across a multi-phase agile programme.
Key Responsibilities
* Capture end-to-end scientific workflows spanning compound management, assay data, and multi-omics (RNA‑Seq, scRNA‑Seq, proteomics) and translate into user stories, functional specs, and acceptance criteria
* Articulate non‑functional requirements across data governance, access control, regulatory traceability, and FAIR data principles
* Collaborate with Solution Architects on cloud‑native platform architecture — defining API contracts, data flows, and integration logic across LIMS, ELN, and CDW systems
* Support definition of entity resolution logic (deterministic, NLP, and LLM‑assisted matching) from a functional perspective
* Own backlog grooming and sprint ceremonies across iterative delivery, acting as primary functional escalation point during build and integration
* Define and execute SIT/UAT validation scenarios covering data normalisation, pipeline performance, and scientist‑facing workflow behaviour
Skills & Experience
* Proven BA experience on data or platform programmes in life sciences or pharma R&D
* Domain fluency across omics data types, biomarker discovery, or translational research workflows
* Familiarity with research informatics systems — LIMS, ELN, CDW, or equivalent
* Understanding of cloud‑native data architectures — data lakes, APIs, and integration patterns (Azure, AWS, or GCP)
* Working knowledge of ML/AI concepts — NLP, entity resolution, vector search, and active learning
* Agile delivery experience across multi‑release programmes with continuous requirements refinement
* Confident communicating with PhD-level researchers, R&D leads, and C‑suite stakeholders
Working Model
Reports to Delivery Manager / Product Lead. Collaborates daily with Architecture, Engineering, QA, and client‑side scientific stakeholders.
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