Senior Product Manager, Data & AI Corporate Functions (HR & Legal)

About the Role

We're building HR and Legal data products that power workforce planning, talent strategy, compliance, and risk management across the enterprise. These products unify data from core systems such as Workday, Agiloft, SFDC, ServiceNow, and are delivered through a unified enterprise analytics and intelligence platform: a trusted single source of reference that exposes insight through APIs, semantic models, dashboards, and conversational and agentic AI experiences.

As Product Manager, you'll help drive the data and analytics product strategy and roadmap for our Corporate Functions (HR and Legal). You'll partner closely with stakeholders to understand their strategic priorities, operating rhythms, and pain points — fragmented data, manual reporting, limited scenario planning, and governance gaps — and translate them into high-impact, AI-enabled data products that sharpen insight, automate reporting, and elevate HR and Legal as strategic advisors to the business.

This role sits at the intersection of data engineering, business strategy, and applied AI. You'll turn complex business needs into a clear product roadmap while working hand-in-hand with data engineers to ship scalable, reliable, and high-impact solutions.

This is a high-visibility, cross-functional role for someone who can operate at both strategic and technical depth, partner effectively with engineering and business stakeholders, and who has hands-on experience shipping AI/ML-powered products.

What You'll Do

• Partner & advise: Build trusted relationships with HR and Legal stakeholders, understanding their objectives, operating cadence, and core processes. Translate pain points (attrition risk, skills and talent strategy, DEI reporting, contract bottlenecks, compliance governance) into data product solutions and manage expectations within and across functions.
• Shape strategy & roadmap: Drive the product strategy and an ROI-informed roadmap, balancing quick-win delivery against foundational platform work, technical debt, and scalability.
• Build data products: Own function-grade semantic models that integrate with the enterprise platform, model store, and query APIs. Productize analytics and AI/ML services while upholding platform principles: system of reference, domain data ownership, and full lineage, provenance, and auditability.
• Deliver end-to-end: Lead delivery from problem framing and data feasibility through model evaluation, deployment, and adoption. Build prototypes, define test cases and UAT, run agile release cycles, and ensure data quality, security, and compliance on everything shipped.
• Analyze the market: Track industry practices and emerging HR and Legal analytics and AI trends (predictive attrition, skills intelligence, contract analytics, compliance automation), and bring in best-in-class governance frameworks (GDPR, data privacy, records compliance).
• Build business cases & measure success: Develop financial models and opportunity reviews, and define the metrics that prove product value (adoption, reporting cycle-time reduction, forecast accuracy, model quality, automation ROI).
• Collaborate cross-functionally: Work hand-in-hand with data platform, data science, AI/ML, and engineering teams on pipeline design, backlog refinement, and product training.

What You'll Bring

• 8+ years of product management experience (3+ years as a Data Analyst/similar role supporting cross-functional global business units, for candidates coming from an analytics background), with at least 2–3 years focused on data platforms, analytics, or AI/ML products.
• Bachelor's degree preferred in Statistics, Data Science, Engineering, Economics, Business, or a related field.
• Strong technical fluency: enterprise data platforms, semantic and data modeling, ETL/ELT pipelines, APIs, and the AI/ML lifecycle (data prep, training, evaluation, deployment, monitoring). Comfortable with SQL and hands-on data analysis.
• Demonstrated experience shipping AI/ML-powered products (predictive models, LLM-based applications, automation tools).
• Solid grasp of data governance: lineage, provenance, auditability, and domain data ownership.
• Knowledge of HR and/or Legal concepts (workforce planning, people analytics, compliance, data privacy, contract lifecycle management) is a strong plus.
• Excellent communicator who can simplify the complex, flex between technical depth and business storytelling, and build trust across HR, Legal, IT, Engineering, Data Science, and AI/ML teams.
• Bias for action and ownership: breaks down complex problems, drives alignment, and stays decisive.