Senior Business Analyst – Biologics Discovery Platform

Introduction to role

Are you ready to turn complex discovery science into AI-ready, scalable platforms that accelerate medicines to patients? Based in Kendall Square, MA, this role connects scientists at the bench with robust digital foundations that drive speed, quality, and reproducibility across early biologics discovery. As Senior Business Analyst, you will partner with Biologic Engineering scientists, senior leaders, and program managers to shape high-impact cases, define rigorous requirements, and orchestrate lab and data-flow automation that powers smarter experimentation and portfolio decisions. You will ensure solutions meet quality and compliance standards while delivering measurable value and seamless integration across teams. Do you thrive at the intersection of science, data, and product strategy? You will operate with autonomy while aligning cross-functional teams worldwide, mentoring Business Analysts, and embedding Scaled Agile practices to move from idea to delivery with clarity and pace.

Accountabilities

• Backlog Ownership and Demand Management: Own and prioritize the team backlog; establish demand management for lab and data-flow automation to create AI-ready pipelines that increase discovery velocity and data quality.
• Requirements Elicitation and Analysis: Facilitate workshops and partner interviews across target identification, screening, and lead optimization; translate needs into epics, user stories, and acceptance criteria that drive clear delivery outcomes.
• Value-Driven Delivery and Scaled Agile Leadership: Partner with scrum masters to refine backlogs, prioritize value, and convert user stories into implementable tasks; embed Scaled Agile practices that balance near-term delivery with platform scalability.
• Process Architecture and Continuous Improvement: Map and maintain end-to-end processes to ensure clarity, compliance, and reproducibility; champion continuous improvement with measurable impact.
• Roadmapping and Portfolio Alignment: Shape multi-quarter roadmaps and prioritize initiatives using value, risk, and dependency analysis aligned to discovery landmarks and portfolio goals.
• Collaborator Partnership and Communication: Build trusted relationships across discovery science, platforms, data and analytics, and engineering; provide transparent status reporting, decision logs, and alignment forums.
• Problem Structuring and Decision Support: Turn ambiguous scientific and operational challenges into structured problem statements, options, and decision frameworks; present trade-offs with quantified impacts to advise senior decisions.
• Traceability, Testing, and Release Quality: Maintain traceability from business objectives to user stories, acceptance criteria, test cases, and release notes to ensure compliant, auditable delivery.
• Cross-Functional Integration: Coordinate across discovery labs, data and AI teams, automation engineering, and platform technology groups to manage dependencies and deliver integrated solutions.
• Risk Management and Scenario Planning: Maintain risk registers, run scenario analyses, and recommend critical issues based on evidence and quantified outcomes.
• Coaching and Community Building: Mentor Business Analysts and scientists in requirements hygiene, story writing, and value tracking; contribute playbooks, templates, and communities of practice.

Essential Skills/Experience

• Minimum 6+ years’ experience working with complex integrated systems, preferably in molecular biology and antibody discovery in a pharmaceutical research organization
• Bachelor's Degree or equivalent experience; preferably in a relevant field
• Demonstrable experience of successfully deploying a variety of business analysis tools & techniques to enable business change; adept at virtual collaboration to lead, shape and develop innovative solutions
• Experience shaping product visions, defining value hypotheses, outcomes, and success metrics; able to balance short-term delivery with long-term platform scalability
• Strong engagement, communication, and collaborator management skills across scientific and IT partners
• In-depth knowledge of computational and experimental techniques used within biologics discovery
• Skilled in analysing and documenting end-to-end data flows, including profiling, mapping, and how data is analysed
• Ability to manage high levels of risk by making complex judgements, developing innovative solutions, and applying a comprehensive multi-functional and industry understanding

Desirable Skills/Experience

• Experience with Atlassian based software management tools (e.g. Jira, Confluence)
• Comfort with low fidelity prototyping, journey mapping, and usability testing to ensure solutions fit scientist workflows.
• Contracting and vendor governance including developing measurable acceptance criteria and ability to govern vendors against outcomes rather than activity
• Understanding of lab automation ecosystems (e.g., scheduling, liquid handlers, plate readers) and how instrument data flows into ELN/LIMS and analytics.
• Good understanding of industry technology trends regarding Agentic AI.