Product Manager/Product Owner — Enterprise Analytics/AI/ML

Sanofi•Cambridge, MA

1d•$178,500 - $257,833•Onsite

About The Position

Sanofi is undergoing a significant digital transformation, with a focus on accelerating data adoption and implementing AI/ML solutions to enhance R&D, manufacturing, and commercial performance. A key initiative is the modernization of US Gross-to-Net (GTN) capabilities, transitioning from manual processes to AI-powered insights and forecasting. This role involves leading a portfolio of AI and analytics products for the US GTN function, specifically focusing on three strategic products: GTN CLARITY, GTN COMPASS, and Dynamic GTN Forecasting. The Product Owner will define the product vision, strategy, and roadmap, ensuring alignment with various business teams. The role requires deep expertise in AI/ML-driven analytics, strong product leadership, and the ability to develop solutions for complex, regulated environments. The position is part of the Global Digital GBU Advanced Analytics & AI Team, operating in cross-functional pods and fostering collaboration to maximize value and efficiency. Sanofi aims to be an AI-first organization, utilizing a leading-edge tech stack and offering world-class mentorship.

Requirements

Bachelors degree with 7+ years of experience in digital product management, with a strong track record of delivering end-to-end analytics platforms, data products, or AI/ML solutions at enterprise scale - required.
5+ years leading complex digital transformation programs in large, matrixed organizations — ideally spanning data engineering, advanced analytics, and AI/ML product development - required.
Demonstrated ability to translate ambiguous, complex business problems into structured product roadmaps and scalable technical solutions.
Proven experience managing multi-vendor delivery environments including RFP processes, Systems Integrator selection, and external partner management.
Strong understanding of enterprise data architecture concepts including data mesh, data lakes, cloud platforms, and connected data foundations.
Exceptional stakeholder management skills with executive-level communication and the ability to influence without authority across business and technology functions.
Deep knowledge of Lean/Agile practices, product management frameworks, and UX/UI principles.
Hands-on experience with data engineering and analytics stacks (Python, SQL, Spark, cloud data lakes — Azure, AWS, GCP).
Strong understanding of AI/ML solution design, predictive modeling concepts, and analytics platform architecture.
Experience with forecasting frameworks, scenario modeling, variance decomposition, and reconciliation workflows in complex data environments.
Familiarity with enterprise data platforms (Snowflake, Databricks) and connected data architecture standards.
Ability to work with AI-driven insights, natural language interfaces, and ML-enabled forecasting tools.
Strategic thinker with strong business intuition and ability to connect technical solutions to business outcomes.
Influential leader who inspires cross-functional teams and drives alignment across competing priorities.
Strong problem solver with a "get things done" mindset and comfort operating in ambiguous, fast-moving environments.
Excellent communicator who can translate complex technical concepts for non-technical audiences and vice versa.
English a must

Nice To Haves

Familiarity with financial analytics, forecasting, or reconciliation domains — experience in pharmaceutical commercial analytics a plus but not required.
Experience with EPM platforms (Anaplan, Adaptive Insights, or similar) a strong plus.
French a plus, other languages a plus

Responsibilities

Lead End-to-End Product Delivery: Own the full product lifecycle — from discovery and requirements definition through build, test, and scale — for GTN CLARITY, GTN COMPASS, and Dynamic GTN Forecasting. Drive delivery excellence across cross-functional pods including Data Engineering, Data Science, UX, and AI teams.
Define and Execute Product Vision: Establish and maintain a clear, compelling product vision and multi-horizon roadmap for a connected GTN analytics ecosystem. Translate complex business challenges into well-defined, prioritized product backlogs that deliver measurable value.
Drive Enterprise Data Transformation: Lead the migration and modernization of fragmented, manual GTN processes onto scalable, AI-ready data foundations. Champion adoption of enterprise data standards (USDF, OneMesh) and ensure architectural decisions support long-term scalability across brands and BUs.
Optimize and Prioritize Use Cases: Identify, assess, and prioritize GTN use cases (retrospective insights, prospective modeling, forecasting, reconciliation, monitoring) based on business value, technical feasibility, and data readiness. Apply structured frameworks to manage trade-offs and sequencing.
Collaborate with Business Stakeholders: Partner with Finance, Pricing, Access Analytics, GTN CoE, Brand GMs, and GTMC teams to deeply understand pain points, co-design solutions, and ensure GTN tools support key governance processes including Actuals Review, Access & Investment Boards, Strategic Access Forums, and bid-cycle preparation.
Manage Vendor and Platform Selection: Lead RFP processes, vendor evaluation, and Systems Integrator selection for Dynamic GTN Forecasting platform. Manage external delivery partners and ensure alignment with Sanofi's enterprise architecture and data governance standards.
Standardize and Scale Digital Products: Drive standardization across GTN workflows, dashboards, forecasting logic, and reconciliation engines to ensure consistency and reuse across brands and BUs. Scale CLARITY to new brands and expand COMPASS capabilities as data foundations mature.
Ensure Performance and Value Realization: Define KPIs, establish measurement frameworks, and ensure measurable business impact through improved GTN accuracy, reduced variance, automation of manual workflows, and enhanced strategic decision-making.
Champion Responsible AI: Ensure all GTN AI/ML solutions are developed and deployed in alignment with Sanofi's RAISE responsible AI framework, maintaining compliance, auditability, and transparency across all products.