Senior Product Manager - Data and AI Platform

Ready to be a Titan? 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 — 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. Proactively identify and resolve disagreements over methodology, ownership, and model quality before they stall multiple teams building on your systems.

5+ years of product management experience, strong track record in enterprise B2B SaaS; experience with at least one of ranking/recommendation systems, entity resolution, or causal inference — this role will likely touch more than one over time. Genuine statistical fluency — comfortable with precision/recall tradeoffs, confounding vs. causation, and model evaluation, regardless of which specific problem you're applied to. Demonstrated ability to define evaluation criteria and "what correct looks like" for a new statistical problem from scratch, rather than working from an existing rubric. Comfort context-switching between different algorithmic domains as customer and business priorities shift. Experience translating customer-reported problems (bad matches, low trust in recommendations, wrong conclusions) into statistically defined product work. Strong communication skills — explaining model tradeoffs to domain PMs, ML engineers, and customers who each need a different level of technical detail. Self-starter who takes initiative and holds themselves accountable to outcomes — "mostly works" isn't good enough when customers are trusting your systems with real decisions. Why This Role Matters: Ranking, deduplication, causal inference — and whatever comes next — quietly decide what ServiceTitan surfaces, trusts, and acts on, for both internal teams and the customers depending on those systems being right. Get it wrong, and the failure isn't loud — it's a customer trusting a bad recommendation, or two records that should've been merged staying separate. Your job is to bring statistical rigor to decisions most PMs never have to make,