Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. About the Opportunity We are seeking a VP of AI Strategy & Transformation — a hands-on technical leader who combines deep AI expertise with the strategic vision and executive influence to drive AI adoption across every business unit. This is not a research role or a traditional engineering management position. We need someone who has personally built and shipped production AI systems, understands the frontier of foundation models and agentic AI, and can translate that expertise into company-wide transformation. The ideal candidate is, first and foremost, a deeply technical AI practitioner — someone who has architected and deployed AI systems at scale, and who can channel that credibility into driving AI adoption across every function of the organization. Not a theorist, not a people-manager-only — a builder-leader who ships and who makes others ship. What You’ll Be Doing 1. Company AI Strategy & Transformation Own the company’s AI roadmap end-to-end — from foundation model selection to business-unit-specific deployment plans: Define and continuously refine the enterprise AI strategy, aligning it to revenue goals, product differentiation, and operational efficiency targets. Conduct rigorous build-vs-buy-vs-partner analysis for f
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Role overview
Job description
We are looking for a hands-on VP, Product Analytics to lead Product Analytics and build an AI-native analytics operating system across the company’s crypto, stocks, prediction markets, perpetuals, and stock futures products.
You will set the analytics strategy, lead and develop the Product Analytics team, and ensure data consistently shapes product and business decisions. This is a player-coach role: you will operate at executive level while remaining technically close enough to review PRs, guide data modeling and pipeline design, and challenge analytical conclusions.
You will own product and business reporting, experimentation, release measurement, diagnostic analysis, the Amplitude data stack, and the systems through which analytics work is delivered at scale.
Set the vision, priorities, operating model, and quality standards for Product Analytics.
Hire, coach, and develop a high-performing team.
Review analytical and data-engineering PRs, providing guidance on SQL, data models, pipelines, metric definitions, and methodology.
Represent Product Analytics in executive and product decision-making.
Allocate team capacity toward the company’s highest-impact opportunities.
Design how analytics work moves from business questions to trusted decisions across intake, data discovery, analysis, validation, reporting, and knowledge management.
Build reusable AI tools to automate repetitive workflows, encode analytical standards, and improve the speed, quality, and consistency of delivery.
Establish appropriate governance, validation, and human review for high-stakes decisions.
Measure the system’s impact on turnaround time, analytical quality, experimentation throughput, and team capacity.
Establish trusted KPIs, source-of-truth metrics, dashboards, and executive business reviews.
Ensure reporting is accurate, consistent, and focused on decisions—not simply monitoring performance.
Partner with Product, Engineering, Data, CRM, Growth, and other functions to align definitions, priorities, and business interpretation.
Make experimentation and evidence core parts of product development.
Establish standards for hypotheses, success metrics, guardrails, experiment design, causal interpretation, and rollout decisions.
Use AI and automation to streamline experiment intake, validation, analysis, and readouts while maintaining analytical rigor.
Help product teams move from opinion-led decisions to repeatable test-and-learn practices.
Own the Amplitude data stack, including instrumentation strategy, event taxonomy, governance, data quality, and integration with warehouse reporting.
Set standards for product instrumentation and ensure new releases can be measured reliably.
Set standards for and review analytical models and pipelines, ensuring metrics remain traceable, reproducible, and trusted as products evolve.
Lead diagnostic deep-dives into activation, conversion, retention, user behavior, market liquidity, trading execution performance, and product health.
Define measurement frameworks and success criteria for major product launches.
Oversee post-release evaluations that inform whether the company should iterate, scale, or stop.
Identify root causes, challenge weak hypotheses, and translate complex findings into clear recommendations and product actions.
Leadership operates from trusted, consistent product and business metrics.
The Product Analytics team has clear priorities, strong technical standards, and consistently high-quality output.
AI-enabled workflows materially improve analytical speed, quality, and capacity.
Product teams use experimentation and evidence as standard parts of development.
Amplitude instrumentation and taxonomy are reliable, governed, and useful.
Major product launches have clear success criteria and rigorous post-release evaluation.
High-impact analyses lead to concrete product, operational, and business decisions.
Proven experience leading Product Analytics teams in a complex, fast-moving organization.
Strong hands-on technical judgment, advanced SQL, and experience with modern data platforms such as Databricks.
Demonstrated experience using AI to redesign analytics operations—not merely improve individual productivity.
Ability to design and implement AI-enabled workflows, reusable agents or tools, validation controls, and analytics knowledge systems.
Experience owning a product analytics platform; deep Amplitude experience is strongly preferred.
Strong knowledge of experimentation, causal inference, product measurement, and diagnostic analysis.
Ability to turn ambiguous business questions into rigorous analysis and clear decisions.
Strong product judgment, people leadership, and executive communication skills.
Consumer fintech, trading, marketplaces, or other transaction-heavy products.
Exchange mechanics, market liquidity, and experience with multi-asset products.
Leading company-wide adoption of new analytics technologies and ways of working.
What they are looking for
Skills & requirements
Department · Product Management & Product Design
Hiring company
Crypto.com
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