Lead Product Analyst – AI Products

HighLevel

. Own instrumentation coverage for the AI pillar by defining required events and properties and driving implementation with product managers and engineering .

Posted 9/21/2026full-timeRemote • United KingdomSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in defining and implementing instrumentation coverage for AI products, establishing KPIs, and driving data-driven decision-making. Proficient in SQL and Python, with a strong background in product analytics and experience in AI/ML feature measurement.

Highest-signal resume keywords

Product Analytics OwnershipEvent Tracking DefinitionAI Experimentation DesignSQL ProficiencyAI/ML Feature Measurement

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Product AnalyticsData ScienceApplied StatisticsEvent TrackingKPI DefinitionA/B TestingSQLPythonAI/ML MeasurementData Analysis

Soft Skills

Cross-Functional InfluenceMentoringStakeholder Engagement

Tools & Technologies

SnowflakeDbtStatsigClaude

Industry Keywords

B2B SaaSCRMProduct-Led GrowthConversational AIVoice AIAgent/Assistant Products

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Own instrumentation coverage for the AI pillar by defining required events and properties and driving implementation with product managers and engineering
Define feature-level KPIs and success metrics for Voice AI, Conversation AI, AI Employee, and Ask AI
Partner with the Experimentation & Causal Inference lead to design and interpret AI experiments, including approaches for non-deterministic systems
Distinguish real signal from instrumentation gaps, novelty effects, and data maturity
Set measurement direction, canonical metrics, instrumentation standards, and contracts for the AI analytics domain
Mentor analysts as the team grows
Translate findings into recommendations for AI product managers and influence the roadmap
Flag data gaps to Analytics Engineering and help shape event taxonomy
Use AI tooling such as Claude for exploration, documentation, and analysis
Establish measurable instrumentation coverage, trusted feature-level KPIs, segmented adoption and quality analysis, rigorous experiment reads, and an analytics foundation for future analysts

Requirements

What you’ll need

7+ years in product analytics, data science, or applied statistics, with hands-on ownership of a product area's metrics end to end
Strong instrumentation instinct; experience defining event tracking/taxonomy and driving it into a product roadmap
Ability to define success metrics for a product from a standing start and gain stakeholder adoption
Fluency partnering on experiments, including A/B design, guardrails, and honest interpretation of results
Strong SQL and working proficiency in Python
Comfort in a Snowflake and dbt environment
Comfort working amid imperfect, in-progress data and consuming governed sources
Cross-functional influence in a fast-moving environment
Experience measuring AI/ML or LLM-based product features, including non-deterministic systems
B2B SaaS, CRM, or product-led growth background
Experience with conversational, voice, or agent/assistant products
Familiarity with Statsig or a comparable experimentation platform
Exposure to AI-assisted analytics workflows

Benefits

Comp & perks

Global, remote-first organization
Opportunity to work on AI products including Voice AI, Conversation AI, AI Employee, and Ask AI
Mentorship and development opportunity through developing analysts as the team scales