Senior Manager Data Science, Revenue & Growth

Checkr
San Francisco, California, United StatesUp to $25kPosted 4 April 2026

Job Description

About Checkr Checkr is building the data platform to power safe and fair decisions. Established in 2014, Checkr’s innovative technology and robust data platform help customers assess risk and ensure safety and compliance to build trusted workplaces and communities. Checkr has over 100,000 customers including DoorDash, Coinbase, Lyft, Instacart, and Airtable. We’re a team that thrives on solving complex problems with innovative solutions that advance our mission. Checkr is recognized on Forbes Cloud 100 2025 List and is a Y Combinator 2024 Breakthrough Company . We're hiring a Senior Manager to lead two connected missions inside Checkr's Data ML organization: (1) own the quantitative backbone of Checkr's revenue and financial data, and (2) accelerate growth on our self-serve SMB business through data science and experimentation. The Revenue side of the role owns forecasting, revenue, and cost data models. These are the sources of truth for business metrics (upsell, churn, unit economics), as well as analytical support for pricing, packaging, and strategic finance. The Growth side owns PLG data science for our SMB segment, which is material to our business and growing fast . We believe there is significant untapped upside in activation, conversion, and expansion. You will build and run the team that nails and captures it. This role sits in the central Data ML team within the Engineering organization. You will partner daily with Engineering, Product, RevOps, Marketing, Finance, and Executive teams. You'll also be a member of the Data ML leadership team, which means you'll be directly involved in shaping Checkr's AI strategy, including our initiative to deploy our agentic fleet and build scalable context with our semantic layer. We are looking for someone based in San Francisco who has built and run data teams in fast-moving, impact-first environments. Less process, more shipping / less paperwork, more results. What you’ll do Build and run the team. Hire, develop, and retain a high-performing group of data scientists and analysts across Revenue and Growth; set clear expectations, coach directly, and create an environment where strong ICs do their best work. Own the revenue data layer. Drive the roadmap for financial data science: revenue forecasting models, cost and billing data products, reconciliation pipelines, and Exec dashboards that our C-staff and board rely on for planning and strategy. Accelerate SMB growth. Lead the PLG data science push: experimentation, activation, and conversion analytics, package and pricing optimization, and propensity models that move self-serve revenue. Partner with Finance and Growth leadership. Be the go-to quantitative thought leader for the CFO org and Product leadership team; translate complex modeling work into clear recommendations that shape our roadmaps. Ship AI-powered workflows. Put AI to work on your team's processes: automate analytical pipelines, build agentic workflows for recurring analyses, and contribute reusable skills and context to Checkr's agentic platform. The expectation is that our teams operate AI-first. Raise the technical bar. Set and enforce standards for modeling rigor, data quality, pipeline reliability, and production-readiness. Your team's outputs inform board-level financial decisions; accuracy and trust are the baseline. What you bring A Bachelor's or Master's degree in a quantitative field (Statistics, CS, Economics, Math, Engineering) or equivalent depth from experience 10+ years in data science, analytics, or quantitative roles, with clear progression in scope and impact 3+ years of direct people management, with demonstrated ability to hire strong talent and develop ICs into high performers Deep SQL and Python fluency; hands-on experience with modern ELT/data transformation tools (dbt, Snowflake, or equivalent); working knowledge of ML and forecasting methods Comfort with and enthusiasm for AI-assisted workflows; experience using ... (truncated, view full listing at source)
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