Product Data Lead

Product Data Lead

At GoodHabitz, we are building an activation-first product strategy that helps learners start, stick, and get value fast — across both LMS-integrated and native platform experiences. We are hiring a Product Data Lead to found and shape the product data discipline from the ground up. This role goes beyond analysis: you will design the event taxonomy, instrumentation standards, and modeled analytics foundations that make product decisions measurably defensible. You will partner closely with Product and Engineering to turn messy, fragmented data into a trusted system (funnels, cohorts, retention), and install a repeatable metrics ritual that enables leadership to steer activation → engagement → retention → GRR with clarity. As the discipline matures, you will help define how product data scales — through systems, processes, and potentially team expansion — based on demonstrated impact rather than pre-set headcount.

This role reports to the Director of Product and will have high visibility across product and executive leadership.

Key Responsibilities

Product Data Foundations (Taxonomy + Instrumentation)

• Define and drive adoption of a product event taxonomy and naming conventions for the highest-leverage activation surfaces.
• Partner with engineering to implement and maintain a tracking plan, including clear ownership and change management.
• Establish instrumentation quality monitoring so broken or missing events are detected early.
• Create clear documentation so teams can use events consistently across products and regions.

Activation & Retention Measurement (Funnels + Cohorts)

• Build a working activation funnel that supports segmentation (LMS vs Platform, coach vs no coach, key cohorts), and is used in product reviews.
• Create D0/D7/D14 (and beyond) retention tracking for key cohorts with explicit cohort definitions and repeatable models.
• Translate product questions into robust analysis patterns, and teach teams how to self-serve.

Executive Narrative & Metrics Ritual

• Install a monthly or bi-weekly product metrics ritual with a small set of agreed metrics, definitions, and owners.
• Produce a clear "Activation → Engagement → Retention → GRR" measurement narrative that leadership can rely on.
• Surface risks and data integrity gaps early, and propose sequencing to resolve them.

Cross-Functional Partnership & Structural Enablement

• Clarify the working model between product data, analytics engineering, and domain teams (who builds what, and what gets prioritized).
• Define requirements for critical identifiers and align stakeholders on scope and sequencing.
• Lead the design and sequencing of critical identity plumbing (e.g., account-level joins across product and revenue systems) to enable reliable product → retention analysis.
• Balance speed with rigor: ship practical v1 models and dashboards, then iterate as the system matures.