Senior Compliance Data Scientist

OKX will be prioritising applicants who have a current right to work in Singapore, 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 Building ML systems for compliance at a crypto exchange is a different kind of problem from most ML engineering work. The data spans on-chain transactions, fiat flows, KYC records, and behavioural signals that very few organisations have in one place. The problems are genuinely unsolved, the stakes are high, and the work has direct bearing on how a global exchange detects and responds to financial crime. For someone who wants their engineering work to matter beyond model accuracy metrics, this is an interesting place to be. This role sits within a team of data scientists, analytics engineers, and compliance specialists who are building the analytical and AI infrastructure that powers the compliance function. You will work across the full ML lifecycle, from feature pipelines and model development through to deployment and monitoring, with close involvement from the domain experts who understand what the models need to do in practice. AI-assisted development is how this team works. LLM-assisted coding, automated analytical pipelines, and AI-powered investigation tooling are part of the daily workflow. We are looking for engineers who already operate this way and who can raise the bar for what that looks like in a production compliance environment. 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 anomaly detection methods, and a working knowledge of how those approaches translate to compliance pr

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 anomaly detection methods, and a working knowledge of how those approaches translate to compliance problems.