Our all-in-one software is built for home and commercial contractors to keep all their service visits and construction projects running smoothly. Backed by Battery, Bessemer and Index.
About the role
At ServiceTitan, we're building the operating system for the trades. As we continue to scale, we're looking for a Senior Product Manager to join our Data & AI Platform team and own the algorithmic systems that sit underneath dozens of downstream product features and quietly decide what gets prioritized, surfaced, and trusted across ServiceTitan.
What they're looking for
- Define and own the roadmap for whichever algorithmic systems — ranking, deduplication, causal inference, or similar — are highest-priority based on domain team and customer need
- Translate real customer pain (bad matches, untrustworthy rankings, wrong conclusions drawn from correlated data) into statistically rigorous product requirements
- Co-author PRDs for statistically ambiguous problems where the "right answer" isn't obvious — you're defining the evaluation criteria as much as the solution
- Partner with ML and engineering to evaluate model tradeoffs (precision/recall, false positive cost, explainability vs. accuracy) and make the product call when there's no clean answer
- Set measurable, multi-quarter goals for algorithmic system health and lead cross-functional teams toward them with rigor
- Lead discovery with domain product teams and customers to understand where algorithmic errors actually cost time, money, or trust
More about this role
At ServiceTitan, we're building the operating system for the trades. As we continue to scale, we're looking for a Senior Product Manager to join our Data & AI Platform team and own the algorithmic systems that sit underneath dozens of downstream product features and quietly decide what gets prioritized, surfaced, and trusted across ServiceTitan.
This is a senior individual contributor role for a product leader who thinks in statistics, not just user stories. The specific problems you'll own will shift based on what domain teams and our customers need most — today that might mean ranking methodology, deduplication logic, or causal inference; tomorrow it could be a different statistically-driven problem entirely. What stays constant is the kind of thinking: translating ambiguous, statistically messy problems into clear product requirements that engineering and ML can build against with confidence. This is a heavily stats-driven PM role: you'll be evaluating model tradeoffs, defining what "correct" means for a given system, and defending methodology choices to a technical audience as much as you'll be writing a roadmap.
- Define and own the roadmap for whichever algorithmic systems —...
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