Principal Data Scientist, Risk & AI
Location: San Jose, California, United States
Department: Product Management
Who We Are
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 Team:
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Design and build an AI-first risk analytics framework supporting fraud, identity, payments, growth abuse, and account security risk domains.
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Develop scalable AI systems that convert raw risk signals into automated insights, decisions, and actions.
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Lead the evolution from rule-based and manual workflows toward AI-assisted and AI-autonomous risk decisioning.
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Drive operational efficiency by replacing manual reviews with AI-assisted or AI-led review workflows.
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Collaborate across business and technology stakeholders to communicate analytical findings to both technical and non-technical audiences.
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Partner with 2LOD for risk mitigations and solutions
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Design and implement risk metrics framework across the Risk organization
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Enhance monitoring/alerting solutions across all functions. Develop early-warning systems and leading indicators that detect shifts in risk exposure before they impact the P&L.
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Drive the shift from correlation-based decisions to causality-based strategies.
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Master’s degree (or PhD) in Statistics, Mathematics, Operations Research, Computer Science, Economics, Engineering or other quantitative discipline. Bachelor’s degree with significant relevant experience will be considered.
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8+ years of fraud analytics experience in financial services or FinTechs
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Payment, Crypto/Blockchain experience preferred
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Advanced programming skills of statistical / analytical software (SQL, R, Python,etc.);
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Demonstrated experience building or deploying AI-driven analytical systems, not just standalone models.
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Experience applying LLMs, AI agents, or generative AI to analytical or operational workflows.
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Ability to design AI systems that automate reasoning, investigation, or decision support.
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Experience improving operational efficiency through analytics automation or intelligent tooling.
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Familiarity with prompt engineering, agent orchestration, retrieval-augmented generation (RAG), or decision intelligence systems.
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Successful track record of owning and driving large, complex data analysis projects.
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Deep expertise in Statistics and Probability (hypothesis testing, confidence intervals, distributions). You don't just run the test; you understand the mathematical assumptions behind it.
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Demonstrated capacity for innovation and outside-the-box thinking in the creation of new capabilities and processes that are unstructured or exploratory in nature.
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Exceptional data storytelling skills. The ability to visualize complex data (Tableau, Looker, Streamlit) and persuade non-technical stakeholders
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Experience in a fast-paced startup environment with a strong level of initiative; and
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Ability and willingness to travel as needed.
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Strong communicator in both writing and speaking
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Multi-tasking and strong project management skills
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Hands-on experience/knowledge of modeling in machine learning (GBM, XGBoost, Random Forest, etc.)
Perks & Benefits
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