Business System Analyst

Key Responsibilities

• Partner with business stakeholders (development, clinical, commercial, QC, specifications, tech transfer) to understand how product and process information is created, changed and used, and translate these needs into clear product outcomes for digital product profiles, recipe libraries and PDLM features.
• Define and maintain the product vision and roadmap for digital product profile and recipe-library capabilities in PDLM, aligned to domain strategy and wider CMC / manufacturing digital plans.
• Work with business and tech stakeholders and prioritise epics and features for PDLM and related tools, including new and AI-enabled capabilities, ensuring the backlog reflects business value, risk, effort and dependencies.
• Support practical library management for process actions, material and equipment classes, helping business lines define and maintain these building blocks and encouraging consistent use of agreed recipe and method structures.
• Promote adherence to agreed recipe and method principles (e.g. ISA-88-style building blocks and clear naming), without turning the role into a technical standards owner; ensure that when business teams approve new or changed library items, the digital products support that workflow cleanly.
• Work with Solution and Enterprise Architects to agree design options for PDLM features and integrations so that solutions are secure, scalable, supportable and fit with existing lab, manufacturing and data systems, but does not own architecture.
• Help define simple product measures (e.g. adoption of digital recipes vs legacy documents, reuse of library items, time to update methods/specifications, user feedback) and use these insights to adjust priorities and improve usability.
• Coordinate with LES/LIMS, ERP, MES, DCS and regulatory systems teams so that the digital product profile and recipe libraries can be consumed downstream for batch execution and digital submissions.
• Help define where PDLM provides the trusted source and how data is exposed or transformed so users and systems do not need to recreate information in multiple places.
• Support adoption and change by working with business champions and Product Owners on communication, training, onboarding and light-touch support materials that explain how digital recipes and product profiles should be used in day-to-day work.
• Make sensible use of AI-assisted tools for analysing feedback, shaping backlogs and preparing product documentation, validating outputs for accuracy, security, GxP/data integrity and maintainability before use.

Basic Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Business, Life Sciences or a related discipline, or equivalent relevant experience.
• 7+ years of experience in product management, business analysis, digital solutions, technology delivery or process-led technology roles.
• Experience working with QC, analytical or regulatory teams on method/specification or quality data problems.
• Experience defining and prioritising epics, features, user stories and acceptance criteria and managing a product backlog.
• Experience working directly with business stakeholders to translate needs into feasible, value-led technology changes.
• Experience guiding Product Analysts, Engineers, Architects and Testers through refinement, design, testing, release and adoption.
• Experience applying security, data protection, quality, validation, change and service-readiness controls.
• Experience prioritising based on value, process impact, risk, cost, capacity and technology dependencies.
• Experience defining product performance measures and using user, process, stability and service insights to improve outcomes.
• Experience working in agile or iterative delivery environments and coordinating suppliers or external delivery partners.
• Exposure to systems that consume product and process data (such as MES, LES/LIMS, ERP or regulatory tools), even at a high level.
• Practical use of AI-assisted tooling (e.g. for analysis, documentation or backlog refinement), applied within Responsible AI, data privacy, cyber security and GxP controls.

Preferred Qualifications

• Product ownership, agile delivery, business analysis, change, process improvement or service management certifications are desirable.
• Clear written and verbal communication, with the ability to explain product decisions and technology constraints to non-technical stakeholders.
• Strong facilitation skills for discovery, backlog refinement, prioritisation, demonstrations and acceptance discussions.
• Analytical judgement to balance value, risk, cost, complexity, urgency and operational impact.
• Ability to interpret process information, user feedback and product data to identify improvements.
• Working understanding of architecture, integration, data, security, validation, service and operational readiness.
• Strong organisation, traceability and documentation discipline.
• Collaborative approach and ability to work across global, cross-functional and supplier teams.
• Commitment to user-centred, capability-led and technology-agnostic solutions.