Manager, Internal Product Analytics

Datadog·New York, New York, USA·onsite
crypto:analyticsproductIC2Product Management
Compensation
Not disclosed
The Internal Product Analytics (IPA) team is the analytics backbone of Datadog's Product organization. With over thirty products on a single platform, IPA gives PMs and leadership the data, tooling, platform, and analysis they need to make good decisions. The team owns the recurring analytical work the Product org runs on and builds the AI-first workflows that make that analysis faster and more consistent across the org. As Manager of the Internal Product Analytics team, you will directly manage a team of data analysts, partner closely with the PMs your team serves, and partner with the associated platform engineering teams. You will set the direction for how the team delivers analysis, builds AI-first tooling, and partners across functions. This is a role for someone who works well across teams, turning complex data and open questions into clear, trusted answers that PMs and leadership can act on. What You'll Do: Guide and grow the Internal Product Analytics team. Manage, coach, and develop a team of data analysts. Set priorities, hold a high bar for quality, and make sure the team's output is trusted across the Product org. Partner directly with the PM org. Work side by side with the PMs your team serves to frame the questions that matter, shape the analysis, and make sure the answers reach them in a form they can act on. Own the recurring analytics the PM org runs on. Business reviews, feature request analysis, usage and adoption tracking, and pricing analysis. Make this work consistent, repeatable, and fast so PMs get answers when they need them. Build AI-first analytics. Design and ship AI-powered workflows and agents that do the heavy lifting of analysis, from data querying to synthesis to reporting. Set the standard for how the team uses AI so analysis scales without simply adding headcount. Partner across functions. Work with Finance, Data Platform, Engineering, and Revenue teams to align on definitions, source the right data, and turn raw signals in