Senior Product Manager

As SPM for User Identity and Profiling, you will own the product strategy and execution for the company's identity infrastructure and user profiling platform. This is a foundational platform role: your work will unlock personalisation, improve recommendation accuracy, reduce friction in return journeys, and give the company a durable data asset at the household level.

The candidate will have responsibilities across the following functions:

User identity platform:

• Define and own user identity model: anonymous-to-known resolution, cross-session stitching, cross-vertical identity unification, and household-level aggregation.
• Own the identity graph product requirements: entity resolution, deduplication logic, confidence scoring, and merge/split rules.
• Design identity persistence across channels: web, app, partner white-label, and inbound call/agent flows.
• Own the privacy and consent architecture: what data is captured, how it is stored, what user controls exist, and how consent propagates across the platform.
• Ensure the identity layer meets Australian privacy and data handling standards relevant to the verticals.

User profiling and household model:

• Define the household profile schema: what attributes are captured, inferred, and maintained across Energy, Telecom, Insurance, and Finance verticals.
• Own the profile completeness and freshness model: how profiles are built over time, how stale data is flagged, and how users can view and update their own profiles.
• Define the event taxonomy and data capture requirements that feed the profiling engine, in partnership with the Data Engineering team.
• Build the product foundation for proactive recommendations: what signals trigger a recommendation, what confidence threshold is required, and how recommendations are surfaced.

Identity as a platform service:

• Package identity and profiling as internal platform APIs consumed by vertical PMs, the recommendation engine, and AI features.
• Define service contracts: what the identity API provides, what data consumers can query, and what change management process applies.
• Own the identity SDK or integration layer for white-label partners who need to pass user context into the company.
• Establish identity data quality metrics: completeness rate, resolution accuracy, stale profile rate, and cross-vertical linkage coverage.

Personalisation foundation:

• Work with vertical PMs and the AI/Automation SPM to define how profile data powers personalised comparison surfaces, pre-filled forms, and contextual recommendations.
• Define the personalisation feedback loop: how user actions update the profile, how recommendation outcomes are measured, and how the model improves over time.

Requirements:

• 6-10 years of Product Management experience with a strong focus on identity systems, user profiling, personalisation platforms, or customer data platforms (CDPs).
• Has owned an identity or profiling platform in a consumer-tech context: login/auth infrastructure, user graph, or household/account modelling.
• Experience with anonymous-to-known identity resolution, cross-device stitching, or session continuity problems in high-traffic consumer products.
• Demonstrated understanding of privacy-by-design: consent management, data minimisation, and user-facing data controls.
• Background in FinTech, InsurTech, e-commerce, marketplace, or aggregator platforms preferred. Comparison or subscription-switching context is a strong plus.

Technical and data fluency (must-have):

• Comfort specifying data models, entity relationships, and schema evolution requirements as product artefacts.
• Working understanding of identity graph concepts: entity resolution, probabilistic vs deterministic matching, confidence scoring.
• Ability to write clear data product requirements: event schemas, API contracts, data quality SLAs.
• Familiarity with CDP architecture, data pipelines, or event-driven data capture patterns enough to partner credibly with data engineering.

Capabilities and ways of working:

• Long-horizon thinker: identity is a foundation, not a feature. Must be able to hold a 2-3 year architecture view while shipping incrementally.
• Privacy-first instinct: thinks about data collection and user consent before thinking about what data would be nice to have.
• Platform mindset: builds for reuse across verticals, not for the nearest vertical asking for it.
• Data-literate: can work directly with data engineers and analysts to define, validate, and measure profile quality.
• Cross-functional influence: identity touches every vertical, and every team must drive alignment without owning everything.

Tools and education:

• Jira, Confluence, and modern PM tooling.
• Familiarity with identity tooling (Auth0 Okta, or equivalent), CDP platforms (Segment, mParticle, or equivalent), and data pipeline concepts.
• Bachelor's degree in Engineering, Computer Science, or related field preferred.