Senior Product Manager, People Product

About This Role

This Senior Product Manager role focuses on owning the internal compensation products, including the tooling, data, and AI that determine how DoorDash sets and maintains pay ranges across various job families, levels, and countries. The core responsibility is to transform the range-setting process into a product: a workspace that ingests market and internal data to enable Compensation Partners to review and make decisions. This is an individual contributor role with a clearly scoped product area, anchored by the range-setting tool and monitoring dashboard.

Responsibilities

• Own product decisions for the compensation range-setting stack, including the range tool, its recommendation engine, and the monitoring dashboard
• Partner with Compensation on methodology while owning how that methodology becomes product logic
• Define the data pipelines and data products that range setting depends on, such as historical ranges, offers, incumbent, and attrition data
• Own the partnership with People Analytics on the semantic layer and the proposed compensation data mart, including product requirements
• Own the range-setting product and analytics roadmap end to end and carry launches to market, including adoption, enablement, and change management
• Improve Compensation Partner productivity across the range review process
• Manage intake, prioritization, and requirements definition for this part of the compensation stack
• Own the seams into adjacent compensation products, such as recruiter offer guidance, budget modeling, headcount planning, and Workday range loads

Requirements

• 5+ years of product management experience shipping products end to end, including at least one data- or workflow-heavy internal or B2B product
• Demonstrated success turning a manual, judgment-heavy operational process into a product with rules, guardrails, recommendations, and measurable throughput gains
• Strong analytical skills and comfort in data: ability to size problems, define evaluation metrics for recommendation engines, understand precision-and-recall trade-offs, and differentiate between anomalies and statistically meaningful signals
• Experience shipping an AI- or model-assisted feature where output quality is the product, including rule or prompt design, evaluation sets, and honest measurement against human decisions
• Excellent partnership and communication skills, including with partners whose day-to-day judgment the product is encoding
• Experience working across custom-built tools and third-party SaaS (HRIS, ATS, survey and benchmarking, BI), including integrating data across systems and negotiating dependencies with platform and analytics teams

Nice to have:

• Direct experience with Compensation or Total Rewards, including range architecture, market pricing, survey data, compa-ratio, peer groups, leveling, or annual budget planning