Manager, Product Analytics & Data Science

Hi, we’re CompanyCam .

We’re a simple-to-use photo documentation and productivity app for contractors of all commercial and home services industries. Packed with intuitive functionality, CompanyCam facilitates unparalleled communication and accountability across a contractor’s entire business. We’re committed to providing a consumer-grade, game-changing experience that helps our users build trust within their company and with their customers.

But don’t let that corporate description fool you—the people behind our buttoned-up product are laid-back (but hardworking), genuine, and kickass, and you could be one of them!

The Role

We’re looking for a Manager, Product Analytics & Data Science to lead and evolve our Product Analytics and Data Science function into a trusted operating partner for Product and Engineering. Reporting to the CFO, this role leads a team of Product Data Analysts and an embedded Data Scientist while remaining close enough to the work to shape analysis quality, support critical product decisions, and guide practical applications of data science across the product organization.

This role is equal parts people leadership, operating model design, product analytics strategy, and practical data science leadership. You’ll help transform the function from a reactive support team into a scalable system for product intelligence — improving experimentation, metric quality, product insights, and decision-making across the business.

You’ll partner closely with Product, Engineering, Analytics Engineering, Data Engineering, and ML/AI teams to build durable practices, clarify ownership, and create a more effective support model for product analytics and data science work.

Location: This is a remote position. You must live and work permanently in the U.S. to be considered.

What You'll Do

• Lead and develop a team of Product Data Analysts and an embedded Data Scientist through coaching, prioritization, and hands-on analytical leadership
• Establish clear expectations and quality standards for product analytics, experimentation, and data science work
• Build scalable operating processes for intake, prioritization, stakeholder communication, and cross-functional collaboration
• Partner with Product and Engineering leaders to support data-informed product strategy and decision-making
• Help teams connect product behavior to activation, adoption, engagement, retention, and customer value
• Guide experimentation strategy and ensure rigorous A/B testing methodologies and actionable interpretation of results
• Improve product metrics and scorecards that measure product health, workflow usage, launch performance, and customer outcomes
• Enable thoughtful self-service analytics through tools such as Metabase, Amplitude, Secoda, and dbt
• Partner cross-functionally with Analytics Engineering, Data En