Sr Data Scientist, Compliance

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 This is a role for someone who finds financial crime problems genuinely interesting. At a global crypto exchange, the compliance data landscape is more varied and more analytically demanding than in most financial institutions: on-chain transaction data, cross-jurisdictional exposure, emerging typologies, and a regulatory environment that is still being shaped. The analytical work here is not about maintaining existing models or running standard reports; it is about building the detection capability and analytical intelligence that the compliance function depends on. You will join a team of data scientists, ML engineers, and analytics engineers working closely with compliance specialists across AML, sanctions, KYC/KYB, and transaction monitoring. The role offers a good balance between deep technical work and meaningful engagement with the domain experts who understand what the outputs need to achieve. It suits someone who is comfortable moving between a complex modelling problem and a conversation with a compliance analyst about what a result actually means. AI-assisted analysis is already part of how this team works. We use LLM tooling to accelerate coding and investigation workflows, automated pipelines to replace repetitive analytical tasks, and AI-augmented approaches to surface patterns faster. We are looking for data scientists who already work this way and who can bring that fluency to hard compliance problems, helping the team do better work rather than learning the basics on the job.     What You’ll Be Doing Develop and validate analytical models and detection strategies for compliance use cases including AML typology detection, customer risk rating, KYC/KYB risk scoring, transaction monitoring calibration, and SAR analytics, working closely with ML engineers on feature design and production implementation. Translate compliance and regulatory requirements into well-defined analytical problems, working with compliance stakeholders to understand what the models need to detect, where current approaches fall short, and what good performance looks like in practice. Conduct exploratory analysis on on-chain and off-chain datasets to surface patterns, validate hypotheses, and develop candidate features for detection models, using AI-assisted tooling to accelerate the cycle from hypothesis to validated insight. Apply AI-assisted coding and automation as standard practice: using LLM tools to write, review, and improve analytical code; building automated workflows that reduce manual query cycles; and contributing to AI-augmented investigation tools that help compliance analysts work through alerts and cases more effectively. Work with ML engineers and data engineers to ensure analytical work is designed for production, reviewing feature logic, validating data quality assumptions, and providing the domain context that engineers need to build pipelines that behave correctly. Maintain clear documentation for models and analyses, capturing methodology, data lineage, and performance metrics to the standard required for internal review and regulatory scrutiny. Support regulatory lookbacks, audit responses, and ad hoc investigations by surfacing relevant data, conducting targeted analysis, and presenting findings to compliance and legal teams in a clear and well-evidenced way. Stay closely engaged with developments in compliance data science: graph ML, LLM-based investigation tools, anomaly detection, and evolving AML typologies in crypto and fiat environments, with an eye toward what is genuinely production-ready versus what is still experimental.   What We Look For In You 8+ years in data science, quantitative analytics, or a related field, with experience working on compliance, financial crime, or regulatory analytics problems in financial services, fintech, or a crypto exchange. We welcome candidates across seniority levels; scope and responsibilities will be aligned with your experience. Solid Python and SQL, with applied experience in machine learning across supervised, unsupervised, and anomal