Senior Product Manager, Identity ProductsAbout the roleWe are looking for a Senior Product Manager to build and take to market a new category of products at Socure: proactive identity notifications. These are subscription products that continuously monitor identities on our customers' behalf and push an alert when something material about that identity changes.
This is a zero-to-one role with a near-term launch. You will own the first product in this line end to end: defining what good looks like, closing any performance gaps that stand between us and a product customers will pay for, shaping the event contract and subscription model, and running it from beta through GA. More event types will follow close behind, and the scope will continue to expand as the portfolio grows.
Data is the heart of this role. The quality of a proactive notification product is the quality of the data underneath it: how much of the real world it sees, how accurate it is, and how quickly it knows. You will own that. You will establish the performance metrics that define success, decide what we need to source and what a candidate source has to prove, and make the call on which sources have earned their place and which have not. A dedicated Data Partnerships team runs discovery, negotiation, licensing, and vendor management against the brief you set, alongside data science and engineering.
You will also own commercialization. Pricing and packaging, commercial terms, early-adopter recruitment, beta and GA phasing, enablement, and coordinating every function to a launch date all sit with you.
This is a highly technical and highly commercial role. It suits a PM who is equally comfortable arguing about precision and recall methodology with a data scientist in the morning and defending a pricing model to the executive team in the afternoon.
What you'll doProduct definition and launch- Own the roadmap, definition, and launch of proactive identity notification products, from first beta customer through general availability.
- Define the customer-facing event contract: what the notification contains, its lifecycle semantics, and how customers consume and act on it.
- Design a systematic customer feedback loop so every notification we send makes the next one better.
- Begin the product definition for the next event types on the roadmap, where the customer problem is more open-ended and the framing work is still to be done.
Data source strategy- Own what we source and why: define the gaps in our coverage, specify what a candidate source must prove, and set the bar it has to clear. Data Partnerships runs discovery and commercial negotiation against that brief.
- Run rigorous, hypothesis-driven evaluations that measure incremental lift rather than headline coverage claims, and make the buy, build, or walk-away call.
- Specify the licensing, retention, and derivative-use terms the product needs, and treat them as first-class inputs to every sourcing decision rather than an afterthought. Legal, Data Protection, and Data Partnerships paper the deal.
- Hold the portfolio to its KPIs: decide which sources have earned their cost, which need renegotiating, and which to retire.
Performance measurement and KPIs- Define and instrument the KPIs for this product line, including coverage, precision, and recency, and build the internal benchmarking capability to measure them independent of customer-reported feedback.
- Go a step further than measurement: define the target for each KPI that constitutes winning in the market. This requires competitive benchmarking and direct customer research, and it is the most important judgment call in the role.
- Quantify the incremental value a subscriber receives per period, and use it to inform pricing and positioning.
- Use SQL and analytics tooling to interrogate the data yourself rather than waiting on someone else's analysis.
Architecture and platform partnership- Partner with platform engineering teams to define how identity signals are resolved, merged across sources, and published, and make the architectural tradeoff calls on where that processing belongs.
- Shape a generalized, reusable notification mechanism so each new event type is faster to ship than the last.
- Balance latency, cost, and refresh cadence against the customer value each incremental improvement buys.
Commercialization and go-to-market- Define pricing, packaging, and commercial terms for a subscription product, in partnership with Legal, Finance, and Revenue.
- Identify, recruit, and work hand-in-hand with early-adopter and design-partner customers.
- Establish and track beta and GA phases, and coordinate cross-functional readiness, including end-to-end testing, to a committed date.
- Build the positioning, marketing plan, and sales enablement materials with Product Marketing, and be the internal subject matter expert the field relies on.
Customer and competitive research- Build a firm, evidence-based read on how we perform against market leaders and where our real differentiation lies.
- Understand the bar customers will actually accept, and be willing to say which customers and use cases we should not sell to yet.
- Assess and design around the business risk of getting a high-stakes identity signal wrong.
What you bring- Experience: 5+ years in product management, preferably in identity verification, fraud prevention, data products, or other data- and ML-driven products.
- Data product instinct: Demonstrated experience evaluating, acquiring, and operationalizing acquired data, including designing tests that isolate incremental lift and making the call to walk away when a source doesn't deliver.
- Technical expertise: Strong understanding of APIs, SQL, databases, event-driven architectures, and product architecture generally.
- Analytical skills: Comfortable working with data directly, writing queries, and defining measurement methodology, including precision, recall, and coverage benchmarking, to inform product decisions.
- Commercial judgment on data deals: Has been the product voice in data or technology vendor negotiations; knows what to ask a provider to prove, how licensing, retention, and derivative-use terms constrain what you can build, and when a deal is not worth doing.
- Commercial ownership: Experience taking a product to market, covering pricing, packaging, beta programs, and launch, not just shipping features.
- Product judgment: Ability to balance technical complexity, customer needs, regulatory constraints, and business impact, and to set a defensible bar for "good enough to launch" when no precedent exists.
- Customer focus: Experience working directly with customers, especially in complex or high-stakes environments.
- Communication: Strong ability to explain complex technical and data concepts clearly to both technical and non-technical audiences, up to and including the executive team.
- Collaboration: Proven ability to work cross-functionally with Engineering, Data Science, Legal, and go-to-market teams.
Preferred- Familiarity with consumer data regulatory frameworks such as GLBA and FCRA, and how they shape product and commercial design.
- Experience with entity resolution, identity graphs, or record-linkage systems.
- Experience building a subscription or usage-based data product from zero to first revenue.
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