Senior Data Scientist Risk Strategy
OKX is a leading global cryptocurrency exchange offering a wide range of trading services, including spot and derivatives trading, as well as Web3 solutions.
Maintainer signals as of 8/20/2026
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About OKX
OKX is a global cryptocurrency exchange known for its trading services and financial products. The platform offers a wide range of features, including spot and derivatives trading, staking services, and a user-friendly interface suitable for both beginners and experienced traders.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You identify complex fraud patterns through data mining, apply graph analytics and unsupervised learning, develop machine learning models, communicate findings to technical and non-technical stakeholders, guide engineering integrations, maintain technical documentation, and help implement risk features and models.
Requirements
- Master's degree or PhD in Statistics, Mathematics, Operations Research, Computer Science, Economics, Engineering, or another quantitative discipline
- Bachelor's degree with significant relevant experience may be considered
- Four or more years of fraud analytics experience in financial services or fintech
- Crypto or blockchain experience
- Deep understanding of machine learning algorithms including GBM, XGBoost, and LGBM
- Advanced SQL, R, and Python skills
- Experience leading complex data analysis projects
- Innovation in exploratory data capabilities and processes
- Experience in a fast-paced startup environment
- Willingness to travel as needed
- Strong written and spoken communication
- Project management skills
- Experience with Random Forest and other machine learning models is an advantage
Responsibilities
- Identify complex fraud patterns and technical root causes through data mining and analysis
- Share data mining techniques as a technical subject matter expert
- Maintain technical reference documentation
- Interface with partner technology teams
- Communicate analytical findings to technical and non-technical audiences
- Guide engineering projects involving API integrations and internal data transformations
- Use link and graph analysis to detect connected fraud networks
- Apply unsupervised learning to augment supervised models and detect portfolio anomalies
- Develop machine learning models
- Partner with product and engineering teams to implement features and models
Benefits
- Competitive total compensation package
- L&D programs and education subsidy
- Team building programs and company events
- Wellness and meal allowances
- Comprehensive healthcare schemes for employees and dependants
- Performance bonus
- Long-term incentives
- Medical benefits
- Financial benefits
