VP, Product Analytics
We are seeking a dynamic individual to lead the Product Analytics function as a leading architect in developing an AI-centric analytics ecosystem for our diverse range of products in the crypto, stocks, prediction markets, perpetuals, and stock futures sectors.
In this role, you will craft the analytics strategy, oversee the Product Analytics team, and ensure data drives key product and business decisions. This position requires a hands-on approach where you will operate at both executive and technical levels, actively engaging in reviewing PRs, guiding data modeling and pipeline design, and critiquing analytical outcomes.
You will be accountable for product and business reporting, experimentation, release assessment, management of the Amplitude data stack, and the infrastructure that enables scalable analytics operations.
Key Responsibilities:
Leadership in Product Analytics:
- Develop the vision, strategy, operational framework, and quality benchmarks for Product Analytics.
- Recruit, mentor, and empower a top-performing team.
- Review analytical and data engineering PRs, offering direction on SQL, data models, metric definitions, and methodology.
- Act as the representative of Product Analytics in executive and product-related decision-making.
- Allocate team resources to address the most impactful opportunities within the company.
Creation of an AI-based Analytics Operating System:
- Design the workflow for transitioning analytical insights from business queries to actionable decisions across intake, analysis, validation, reporting, and knowledge management.
- Develop reusable AI tools to automate repetitive tasks, enforce analytical standards, and enhance the efficiency, quality, and consistency of outputs.
- Implement appropriate governance, validation processes, and human oversight for critical decisions.
- Evaluate the impact of the operating system on turnaround time, analytical quality, experimentation velocity, and team productivity.
Ownership of Product and Business Reporting:
- Establish reliable KPIs, primary metrics, dashboards, and executive-level business reviews.
- Ensure reporting accuracy, consistency, and relevance to decision-making rather than just performance monitoring.
- Collaborate with various functions including Product, Engineering, Data, CRM, Growth, etc., to align definitions, priorities, and business implications.
Cultivate a Culture of Experimentation:
- Integrate experimentation and evidence into the core of product development.
- Set standards for hypotheses, success metrics, experiment design, causality interpretation, and go/no-go decisions.
- Utilize AI and automation to streamline experiment processes, analysis, and insights while upholding analytical standards.
- Drive product teams from intuition-driven choices to data-supported test-and-learn methodologies.
Management of Analytics Platforms and Data Quality:
- Manage the Amplitude data stack, covering instrumentation strategy, event categorization, data quality, and integration with warehouse reporting.
- Establish standards for product instrumentation to ensure new releases are reliably measurable.
- Define and review analytics models and pipelines to ensure metrics remain traceable, reproducible, and reliable during product evolution.
Facilitation of High-Impact Analysis:
- Lead in-depth diagnostic analysis on activation, conversion, retention, user behavior, market health, trading performance, and product well-being.
- Create measurement frameworks and success benchmarks for major product launches.
- Oversee post-release evaluations to inform iteration decisions.
- Identify root causes, challenge weak hypotheses, and translate complex findings into actionable recommendations and product strategies.
Desired Outcomes:
- Leadership based on consistent and trusted product and business metrics.
- Sustained excellence from the Product Analytics team with clear priorities and high-quality deliverables.
- Material improvements in analytical efficiency, quality, and capacity through AI-driven workflows.
- Adoption of experimentation and evidence as cornerstones in product development.
- Reliable and beneficial Amplitude instrumentation and taxonomy.
- Clearly defined success metrics and robust post-release evaluations for major product launches.
- Transformational product, operational, and business insights from high-impact analyses.
Required Qualifications:
- Demonstrated leadership experience in Product Analytics within a dynamic organizational setting.
- Strong expertise in technical judgment, advanced SQL proficiency, and experience with modern data platforms like Databricks.
- Proven track record of leveraging AI to transform analytics operations.
- Ability to design and implement AI-based workflows and tools to enhance analytics efficiency.
- Prior ownership of a product analytics platform, with deep knowledge of Amplitude being highly desirable.
- Excellent understanding of experimentation, causality inference, product measurement, and diagnostic analysis.
- Proficiency in converting ambiguous business challenges into structured analysis and clear decision-making.
- Strong capabilities in product evaluation, team leadership, and executive communication.
Preferred Background:
- Experience in consumer fintech, trading, marketplaces, or transaction-heavy products.
- Knowledge of exchange mechanisms, market liquidity, and multi-asset products.
- Track record of spearheading company-wide adoption of new analytics technologies and practices.
