Senior Business Analyst - Supply Chain

Thermo Fisher Scientific•Pittsburgh, PA

1d•Onsite

About The Position

Thermo Fisher Scientific is seeking a Senior Product Business Analyst to join the Laboratory Products Automation, AI, and Data (AAD) team supporting the Laboratory Products Group (LPG). This role will connect supply chain processes, enterprise data, analytics, artificial intelligence, automation, and technology delivery to drive measurable business outcomes. A key near-term responsibility will be advancing LPG's adoption of Thermo Fisher's global standard supply chain data model. The role will own the business analysis activities required to transition legacy analytics toward modern enterprise data and analytics capabilities and define business-specific extensions where requirements are not addressed by the standard enterprise model. Beyond the data transition, this role will identify, shape, and advance opportunities to apply trusted data through analytics, AI, automation, and digital workflows to improve supply chain decisions, productivity, service, inventory, and working capital.

Requirements

Seven or more years of experience in business analysis, product management, digital transformation, supply chain systems, or a related discipline.
Strong understanding of supply chain processes such as SIOP, demand planning, inventory management, replenishment, procurement, and service performance.
Demonstrated experience leading business analysis across the solution lifecycle, including discovery, process design, requirements definition, acceptance criteria, solution validation, UAT, and release readiness.
Proven ability to identify, shape, and translate business opportunities into scalable data, analytics, AI, automation, or digital solutions that improve business processes and outcomes.
Experience modernizing data, analytics, or business processes within complex enterprise environments, including working across multiple systems, business units, or operating models.
Working knowledge of enterprise data, analytics, AI, automation, and ERP or supply chain technologies, with experience in platforms such as SAP, JDE E1, Oracle, Syspro, Databricks, AWS, or Microsoft Power BI preferred.
Experience applying product discovery, process improvement, design thinking, process mining, user-centered design, or similar methods to identify and shape solutions.
Strong facilitation, communication, problem-solving, and stakeholder-management skills, with demonstrated ability to drive decisions and influence across business and technical teams without direct authority.

Responsibilities

Lead business requirements, gap assessment, validation, and readiness activities required to transition legacy data and analytics to modern enterprise capabilities, prioritizing reuse of enterprise-standard solutions.
Elicit and document business and data requirements, business rules, and acceptance criteria for enterprise data model adoption; partner with data engineering, analytics, and business teams to assess model fit and define required extensions.
Identify gaps requiring business-specific data or analytics capabilities and translate them into scalable functional requirements.
Lead assessment and rationalization of the existing analytics portfolio, identifying duplication and defining migration, consolidation, or retirement recommendations.
Define and validate business definitions, data quality expectations, lineage, and governance requirements to ensure solutions are trusted and fit for business use.
Develop and maintain a deep understanding of supply chain processes, workflows, decision points, pain points, and business outcomes across LPG.
Identify and shape opportunities to improve processes through data, analytics, AI, automation, and digital workflows in partnership with business leaders, process owners, and the AAD leadership team.
Lead discovery and future-state design sessions with planners, buyers, supply chain leaders, process owners, and other stakeholders.
Define future-state processes, decision points, and functional needs, challenging existing ways of working rather than simply digitizing current activities.
Develop value hypotheses, business cases, success measures, and adoption expectations to support demand prioritization and investment decisions.
Research business performance, user needs, industry trends, and emerging technologies to surface potential use cases and contribute to the team's broader opportunity pipeline.
Translate prioritized business opportunities into well-defined use cases, requirements, process flows, user stories, business rules, acceptance criteria, and measurable outcomes.
Define the roles of data, analytics, AI, automation, enterprise applications, and human decision-making within future-state processes, including required governance, controls, traceability, and human oversight.
Lead business discovery, prototype validation, and value assessment to determine whether proposed solutions should progress toward scaled delivery.
Serve as the primary business-analysis interface across business stakeholders and product, engineering, analytics, data, AI, automation, and user experience teams.
Maintain continuity from discovery through design, build, validation, deployment, and post-release support, ensuring delivered capabilities remain aligned to the defined business need and intended outcomes.
Lead requirements clarification, backlog refinement, solution walkthroughs, and functional decision-making within the defined business scope.
Manage functional dependencies and tradeoffs across enterprise standards, business-specific requirements, and legacy capabilities, escalating decisions where appropriate.
Validate delivered functionality against requirements and acceptance criteria before business UAT, documenting gaps and driving functional defect resolution.
Define UAT scope, scenarios, entry criteria, and readiness; coordinate business testers and ensure solutions are sufficiently validated before requesting business acceptance.
Assess release readiness across requirements coverage, defects, process impacts, documentation, user readiness, and operational dependencies.
Develop and coordinate adoption activities with process owners, including pilots, training, communications, office hours, and feedback mechanisms.
Define and track adoption and business-impact measures such as process efficiency, cycle time, decision quality, service, inventory, and working capital.
Monitor post-release performance, user feedback, defects, and enhancement demand; use results to recommend solution, process, enablement, and backlog improvements.
Ensure delivered solutions are usable, supportable, governed, and aligned with agreed business outcomes and enterprise standards.