Principal Product Manager, Data

Principal Product Manager, Data Location: Tel Aviv, Israel (Hybrid) Reports to: Chief Product Officer About the Company Antidote Health is a tech- driven health insurance company on a mission to make healthcare easy, accessible, and more affordable. We’re rethinking how healthcare works—using technology to remove the friction, complexity, and delays that define the traditional system. Instead of navigating paperwork, long waits, and disconnected experiences, we’re building a simpler, more connected way for people to get care. Our platform combines health coverage, virtual care, and a modern member experience into one seamless system designed to help people actually use their benefits. We offer Affordable Care Act (ACA) health plans in Arizona and Ohio, and we’re growing quickly. We’re building a company focused on solving real problems—with real impact on people’s lives. Position Overview Antidote Health is hiring a technical Principal Product Manager to own our data product roadmap: the foundation (self-service analytics, monitoring and alerting, data pipelines for AI and automation) and the products it powers. Those products show how the business is performing and serve our members better, from member retention and population health to risk stratification. You'll work with engineers, data scientists, and analysts based in Israel. Not everything will be in flight at once. A core part of this job is deciding what gets built in what order — sequencing work by business impact, technical dependencies, and team capacity. You make those calls, defend them to stakeholders, and keep the team focused. Your technical depth matters — not because you own the architecture, but because you can challenge technical decisions, understand the real cost of a tradeoff, and write requirements that engineering can execute. For user-facing tools, you know when a product is usable versus technically correct but dead on arrival. Key Responsibilities Roadmap & Strategy (35%) Own a multi-quarter roadmap across the data product and decide what gets built first, rather than advancing everything at once Identify where data creates the most value for users and the business, including opportunities no stakeholder has asked for yet; turn that into prioritized bets Make tradeoff decisions across competing stakeholder needs and defend them Set success metrics for every initiative before a line of code is written Product Definition & Delivery (35%) For each product, define the user problem, who the user is, and what a successful outcome looks like — before engaging engineering on how to build it Work with engineers, data scientists, and analysts to shape the technical approach, surface constraints, and drive to the right solution — not the easiest one Write requirements precise enough for engineering to execute: what the system must do, how it must perform, and how success will be measured Review builds against requirements, identify gaps, and push back where needed For user-facing tools (self-service analytics, risk stratification tooling, population health dashboards), define UX requirements — information architecture, workflow logic, usability standards — with design Drive post-launch iteration — shipped is not done until users are getting value Stakeholder Management (30%) Be the main point of contact between the data team and business stakeholders (operations, CS, clinical, finance, growth) Run structured discovery to surface data needs, test priorities, and set realistic timelines Translate data system constraints into plain language for non-technical audiences Drive adoption of shipped tooling — make sure stakeholders know what was built, why, and how to use it Qualifications Required: 8+ years total, with at least 5 as a PM owning data or platform products Prior experience as a data analyst or software/data engineer — you've written SQL, built pipelines, or shipped analytical systems, which lets you work as a peer with engineering Track record building data foundations and the products they power, with measurable outcomes. Experience in member retention, population health, or risk stratification is a strong plus Able to own a roadmap end-to-end: discovery → scoping → delivery → adoption Enough UX fluency to define usability requirements for user-facing data tools — not a designer, but a PM who knows when something isn't good enough to ship Strong professional English for communication with US-based leadership Strongly Preferred: Experience in a regulated industry — healthcare, insurance, or fintech Familiarity with the ACA market, health plan operations, or clinical data concepts You can read a data model, trace how data moves from source systems to reports, and judge whether a pipeline design will hold up as volume grows Experience at a startup or fast-scaling company where you defined process as much as followed it Experience working with ML/data science teams to ship model-driven data products You Thrive When: Starting with the user problem, not the technical solution — and holding that line when engineering wants to jump straight to implementation Going deep enough into technical details — pipeline architecture, data freshness tradeoffs, system constraints — to make better product decisions Working in a small, senior team where your judgment drives what gets built Pushing back on stakeholders and engineering with structured reasoning, not deference Operating across time zones without losing momentum Building things that last — real adoption, documented decisions, repeatable delivery Success in First 90 Days Deep-dive across the data platform complete — user problems, current gaps, and stakeholder pain points documented Roadmap draft for the next two quarters reviewed with CPO and engineering leadership, with sequencing rationale First initiative scoped end-to-end: user problem defined, success metrics set, requirements written, milestones assigned Working relationships in place with Israel-side engineering and data science leads At least one quick win shipped or in flight, for example: a report that operations or CS now runs themselves instead of asking an analyst, or an alert that warns a team their numbers are wrong before it causes a problem Success in 6-12 Months A current roadmap that stakeholders use and trust Self-service analytics tooling live and used by at least two non-data business teams — adoption tracked Teams find out about data problems before those problems affect members or reports Bots and automation get reliable data, and the teams using them save measurable time Retention and churn data tooling shipped and driving decisions in growth and CS Population health and risk stratification systems scoped, with at least one phase delivered and outcomes measured Equal Opportunity Statement Antidote Health is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, age, disability, marital status, pregnancy, sexual orientation, gender identity, national origin, military reserve duty, or any other protected status under applicable law. 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