Lead Product Analyst - AI Products

Role overview

This role leads analytics for a portfolio of AI-powered product surfaces, including voice, conversational, and assistant features embedded in a multi-product SaaS platform serving agencies, entrepreneurs, and small businesses. The position sets measurement standards, defines instrumentation contracts, and partners with product, engineering, and experimentation teams to make non-deterministic AI features rigorously measurable. It is a senior individual-contributor position with cross-functional influence rather than direct authority over the roadmap.

Responsibilities

- Own end-to-end instrumentation coverage for the AI product pillar: define required events and properties, and drive them into the product roadmap with PMs and engineering - Establish feature-level KPIs and success metrics for voice, conversational, assistant, and AI employee experiences, securing stakeholder alignment - Partner with experimentation and causal-inference leads to design and interpret A/B tests, including approaches suited to non-deterministic systems - Separate genuine signal from instrumentation gaps, novelty effects, and data-maturity issues in every read - Set measurement direction and canonical metrics for the AI analytics domain, mentoring analysts as the pod grows - Translate findings into clear recommendations for AI product managers and influence roadmap decisions without owning them - Flag data gaps to analytics engineering and help shape the event taxonomy the analytics stack depends on - Use AI-assisted tooling to accelerate exploration, documentation, and analysis

Requirements

- 7+ years in product analytics, data science, or applied statistics with hands-on end-to-end ownership of a product area's metrics - Strong instrumentation instinct, including defining event tracking and taxonomies and driving them into a product roadmap - Ability to define success metrics from a standing start and secure stakeholder adoption - Fluency in experiment design (A/B testing, guardrails) and honest interpretation of results - Strong SQL skills plus working Python proficiency, with comfort in Snowflake and dbt environments - Comfort working amid imperfect, in-progress data, consuming governed sources and helping raise the bar - Cross-functional influence: ability to shift PM priorities without direct authority in a fast-moving environment

Nice to have

- Experience measuring AI, ML, or LLM-based product features, including non-deterministic systems - Background in B2B SaaS, CRM, or product-led growth - Experience with conversational, voice, or agent/assistant products - Familiarity with Statsig or a comparable experimentation platform - Exposure to AI-assisted analytics workflows

Benefits and work setup

- Remote-first organization with team members distributed across multiple countries