Senior Product Manager, Analytics & Insights

Position Overview

Autodesk has invested deeply in data‑driven decision‑making to optimize our platform’s business, product, and cloud efficiency. Over the next five years, we expect a significant expansion in data scale and increased adoption of AI/ML to deliver greater value to our customers. As a Senior Product Manager, Analytics & Insights, you will define and drive the product strategy across analytics, data science, and cloud Fin Ops initiatives within the Platform organization.

This is a highly cross‑functional role where you will partner closely with Analytics, Data Science, Engineering, and Fin Ops teams to shape roadmaps, prioritize investments, and deliver data products and insights that drive measurable business impact. You are passionate about solving complex business problems through data and product thinking, proactively identifying opportunities, bringing structure to ambiguity, and ensuring that data initiatives align with platform strategy and outcomes.

The role requires strong influence without authority, as you will work across multiple teams without direct ownership of those functions.

• Define and own the product vision and roadmap for analytics, data science, and Fin Ops capabilities aligned with Platform OKRs.
• Translate business needs into a prioritized backlog of data products, insights, and platform capabilities.
• Partner with Analytics, Data Science, and Engineering teams to deliver scalable analytics solutions, ML‑driven capabilities, and data products.
• Drive the productization of insights, ensuring they are actionable, accessible, and embedded into decision‑making workflows.
• Work with Fin Ops and Engineering teams to define and deliver capabilities for cloud cost visibility, attribution, and optimization.
• Influence cross‑functional stakeholders and senior leaders to align on priorities, trade‑offs, and outcomes.
• Own end‑to‑end delivery of initiatives from problem definition through execution and impact measurement.
• Communicate insights, recommendations, and product direction clearly to technical and non‑technical audiences.

• 8+ years of experience in Product Management in Analytics, Data Science, Fin Ops, or related roles.
• Proven experience owning and delivering data, analytics, or platform products.
• Strong understanding of analytics, data science workflows, and data‑driven decision‑making.
• Experience with data tools and technologies (e.g., SQL, BI tools, Snowflake, dbt).
• Familiarity with cloud platforms (AWS, Azure) and exposure to Fin Ops or cloud cost optimization concepts.
• Strong product thinking and ability to connect business problems to scalable data solutions.
• Excellent stakeholder management and ability to influence without authority.

• Experience in a SaaS or platform engineering environment.
• Exposure to machine learning productization and experimentation (A/B testing).
• Experience with cloud cost management, unit economics, or Fin Ops practices.
• Familiarity with Autodesk’s product ecosystem.

Autodesk a considérablement investi dans la prise de décision fondée sur les données afin d’optimiser l’efficacité de notre plateforme sur les plans commercial, produit et cloud. Au cours des cinq prochaines années, nous prévoyons une expansion significative du volume de données et une adoption accrue de l’IA et du ML afin d’offrir une plus grande valeur ajoutée à nos clients. En tant que chef de produit senior, Analytics & Insights, vous définirez et piloterez la stratégie produit pour les initiatives d’analyse, de science des données et de Fin Ops cloud au sein de l’organisation Platform.

Il s’agit d’un poste hautement transversal dans lequel vous travaillerez en étroite collaboration avec les équipes d’analyse, de science des données, d’ingénierie et de Fin Ops afin d’élaborer des feuilles de route, de hiérarchiser les investissements et de fournir des produits de données et des informations qui génèrent un impact commercial mesurable. Vous êtes passionné(e) par la résolution de problèmes commerciaux complexes grâce à l’analyse des données et à une approche axée sur les produits.

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