VP, Product Analytics

We are seeking a dynamic Vice President of Product Analytics to take charge of product analytics and develop an AI-native analytics ecosystem throughout our organization's various product lines, including crypto, stocks, prediction markets, perpetuals, and stock futures.

The ideal candidate will formulate the analytics strategy, oversee the Product Analytics team, and ensure that data continues to drive product and business decisions. This role requires a combination of executive leadership and technical proficiency to review pull requests, offer guidance on data modeling and pipeline design, and challenge analytical outcomes.

Responsibilities:

Lead Product Analytics

• Define the vision, priorities, operating model, and quality benchmarks for Product Analytics.
• Recruit, mentor, and nurture a high-performing team.
• Review analytical and data engineering pull requests, offering direction on SQL, data models, pipelines, metrics, and methodologies.
• Serve as the representative for Product Analytics in executive and product decision-making processes.
• Allocate team resources towards initiatives with the highest impact.

Establish an AI-native analytics operating framework

• Design the transition of analytics processes from business inquiries to trustworthy decisions across various stages, such as intake, data discovery, analysis, validation, reporting, and knowledge management.
• Develop reusable AI tools to automate repetitive tasks, enforce analytical standards, and enhance the speed, quality, and uniformity of delivery.
• Implement appropriate governance, validation, and human review processes for crucial decisions.
• Evaluate the system's influence on turnaround time, analytical quality, experiment throughput, and team efficiency.

Manage product and business reporting

• Define reliable KPIs, authoritative metrics, dashboards, and executive business reviews.
• Ensure reporting accuracy, consistency, and focus on decision-making instead of merely monitoring performance.
• Collaborate with Product, Engineering, Data, CRM, Growth, and other departments to align definitions, priorities, and business insights.

Cultivate an experimentation culture

• Embed experimentation and evidence as key elements of product development.
• Set standards for hypotheses, success metrics, experiment design, causal analysis, and deployment decisions.
• Utilize AI and automation to streamline experiment processes while upholding analytical rigor.
• Facilitate the transition of product teams from subjective decisions to repeatable test-and-learn methodologies.

Owner of analytics platforms and data quality

• Take charge of the Amplitude data stack, including instrumentation strategies, event taxonomy, governance, data quality, and integration with warehouse reporting.
• Establish standards for product instrumentation and ensure accurate measurement of new releases.
• Define and review analytical models and pipelines to ensure metrics remain traceable, reproducible, and reliable as products evolve.

Drive impactful analysis

• Conduct in-depth diagnostic assessments on activation, conversion, retention, user behavior, market liquidity, trading performance, and product health.
• Establish measurement frameworks and success criteria for significant product launches.
• Supervise post-launch evaluations that inform future iterations, scaling opportunities, or potential discontinuations.
• Identify root causes, challenge weak hypotheses, and translate complex findings into actionable recommendations and product strategies.

Success Indicators:

• Leadership relying on dependable, consistent product and business metrics.
• The Product Analytics team with well-defined priorities, robust technical standards, and consistently high-quality deliverables.
• AI-driven workflows significantly elevate analytical speed, quality, and efficiency.
• Product teams integrating experimentation and evidence into standard development practices.
• Reliable and valuable Amplitude instrumentation and taxonomy.
• Clear success criteria and rigorous evaluations for major product releases.
• In-depth analyses leading to tangible product, operational, and business decisions.

Qualifications:

• Demonstrated experience leading Product Analytics teams in a dynamic and intricate organizational sphere.
• Strong hands-on technical acumen, proficiency in advanced SQL, and familiarity with modern data platforms like Databricks.
• Proven record of leveraging AI to reimagine analytics operations beyond individual productivity enhancements.
• Proficiency in designing and implementing AI-powered workflows, reusable tools, validation controls, and analytics knowledge systems.
• Previous ownership of a product analytics platform, preferably with deep expertise in Amplitude.
• Comprehensive understanding of experimentation, causal inference, product measurement, and diagnostic analysis.
• Ability to transform ambiguous business questions into methodical analyses and decisive strategies.
• Strong product insight, leadership capabilities, and adeptness in executive communication.

Preferred Experience:

• Background in consumer fintech, trading, marketplaces, or transaction-focused products.
• Familiarity with exchange mechanisms, market liquidity, and multi-asset product experience.
• Track record of spearheading enterprise-wide adoption of cutting-edge analytics technologies and methodologies.

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