Senior Data Scientist, Product & Growth Analytics

OKX will be prioritising applicants who have a current right to work in Hong Kong, and do not require OKX's sponsorship of a visa. 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. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About the Opportunity We are looking for a Senior Data Scientist, Growth Analytics, to join our data science team at OKX. Growth is the core mandate of this role — you will own analytics that power how we acquire, activate, and retain users across global markets. You will serve as the analytical backbone for our growth function: measuring channel performance, evaluating the impact of campaigns and promotions, and identifying the levers that move our most important metrics. Beyond analysis, you will design and build AI-powered analytics tools and systems that enable the team to generate insights faster and at greater scale. What You’ll Be Doing Growth Channel Analytics - Own end-to-end measurement of acquisition channels — paid media, referral, affiliate, and organic — tracking performance, efficiency, and ROI; partner with channel owners to surface actionable signals in near real-time. - Build channel attribution monitoring and incrementality frameworks to distinguish true causal impact from correlation. Growth Campaign & Promotion Analytics - Lead analytics for growth campaigns, incentive programs, and promotional events — from pre-launch sizing to post-launch readouts. - Develop incrementality measurement methodologies (holdout tests, synthetic control, difference-in-differences) and build reusable frameworks that reduce time-to-insight for recurring programs. User Lifecycle & Retention Analytics - Partner with growth teams to measure activation, engagement, and monetization across the full lifecycle; build cohort analyses, retention models, and segmentation frameworks to identify high-value segments and growth levers. Experimentation - Design and execute A/B tests; ensure statistical rigor and deliver clear, actionable readouts to growth and product stakeholders. AI-Powered Analytics Tools & Systems - Design and build AI-based analytics tools, agents, and automated insight systems — LLM query interfaces, anomaly detection pipelines, and self-serve tooling that democratizes data access across growth and product teams. - Apply expertise in LLMs, RAG, and agentic workflows to solve real analytical problems at scale; stay current with AI developments and continuously bring new capabilities into the team’s workflow. Stakeholder Partnership - Serve as the primary analytical partner to growth leads and PMs — translating complex analyses into clear, actionable narratives for both technical and non-technical audiences. What We Look For In You Education & Experience - Master's degree in Computer Science, Statistics, Mathematics, Economics, or a related quantitative field. - 5+ years in data science or growth analytics (fintech/crypto preferred), with a demonstrated track record of moving metrics — not just reporting them. Growth Analytics Expertise - Deep experience across the growth analytics stack — channel performance, campaign incrementality, acquisition funnel, cohort retention, and lifecycle segmentation — with strong intuition for what’s working and why. - Familiarity with paid acquisition channels, referral and affiliate programs, and promotional mechanics — and how to measure their true impact. AI Engineering Capability - Proven experience building AI-powered analytics tools or systems — not just using AI assistants, but designing and deploying them (e.g. LLM-based query tools, automated insight pipelines, AI agents for data workflows). - Strong Python; hands-on with LLM APIs, prompt engineering, RAG, and agentic frameworks; able to rapidly evaluate and integrate new AI tooling into production workflows. Technical Skills - Expert-level SQL; proficiency in Python for analysis, modeling, and automation. - Hands-on experience designing and analyzing A/B experiments; solid understanding of statistical inference and experimentation best practices. - Experience building dashboards, self-serve data tools, and automated pipelines; familiarity with