Senior Data Scientist, Risk (Risk Strategy)
OKX
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Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for scientist roles keep coming back to Python, Machine learning, SQL, C++. Practise those questions before you sit with OKX.
Questions you are likely to be asked
- Why do you want to join OKX?
- What is your experience with Machine learning? Tell me one thing you learned the hard way.
- How would you explain your model's result to someone who is not technical?
- What would you check first if a model's accuracy dropped after going live?
- When would you not use machine learning for a problem?
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Practise the Senior Data Scientist, Risk (Risk Strategy) at OKX interview free →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 Opportunity:
- Identify complex fraud patterns and their technical root causes through detailed data mining and analysis, including identification of sophisticated fraud methods employed by actors who are deliberately trying to avoid detection.
- Serve as technical SME by sharing new data mining techniques, maintaining technical reference documentation, and interfacing with partner technology teams.
- Collaborate across business and technology stakeholders to communicate analytical findings to both technical and non-technical audiences.
- Provide technical guidance for engineering projects that incorporate new data points into the investigation team’s toolkit, such as API integrations or internal data transformations.
- Link Analysis/Graph analytics to find and mitigate deeply-connected fraud networks and detect new accounts being added to these networks
- Unsupervised learning methods to augment existing supervised models, or detect portfolio anomalies
- Development of machine learning models
- Partner with product and engineering team in implementing features and models, and enhancing systems
- 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.
- 4+ years of fraud analytics experience in financial services or FinTechs
- Crypto/Blockchain experience
- Deep understanding of modern machine learning techniques / algorithms including GBM, XGBoost, LGBM, etc. Advanced programming skills of statistical / analytical software (SQL, R, Python,etc.);
- Successful track record of owning and driving large, complex data analysis projects.
- Demonstrated capacity for innovation and outside-the-box thinking in the creation of new capabilities and processes that are unstructured or exploratory in nature.
- Experience in a fast-paced startup environment with a strong level of initiative; and
- Ability and willingness to travel as needed.
- Strong communicator in both writing and speaking
- Multi-tasking and strong project management skills
- Hands-on experience/knowledge of modeling in machine learning (GBM, XGBoost, Random Forest, etc.); and
Perks & Benefits
- Competitive total compensation package
- L&D programs and Education subsidy for employees' growth and development
- Various team building programs and company events
- Wellness and meal allowances
- Comprehensive healthcare schemes for employees and dependants
- More that we love to tell you along the process!
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Listed on greenhouse · posted 2026-01-02. ApplySarthi collects openings and links to application pages; the role is advertised by OKX, not by us.