Sr Data Scientist, Risk Strategy

About the Opportunity

The Sr Data Scientist, Risk will offer a strategic perspective, deep analytical and modeling capabilities, and a collaborative working style. The right candidate will have strong intellectual curiosity and passion for achieving business results.

An ability to quickly define the problem, research and leverage state‑of‑the‑art modelling techniques, and provide timely recommendations will be essential. Key skills will include a strong analytical mindset, deep understanding of most popular machine learning algorithms, and the ability to lead key initiatives with integrity and a passion for investigations, problem solving, and troubleshooting.

• 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.
• Perform link analysis/graph analytics to find and mitigate deeply‑connected fraud networks and detect new accounts being added to these networks.
• Apply unsupervised learning methods to augment existing supervised models, or detect portfolio anomalies.
• Develop machine learning models.
• Partner with product and engineering teams to implement features and models, and enhance systems.

• Master’s degree (or Ph.D.) in Statistics, Mathematics, Operations Research, Computer Science, Economics, Engineering or other quantitative discipline; a bachelor’s degree with significant relevant experience will be considered.
• 4+ years of fraud analytics experience in financial services or Fin Techs.
• Crypto/Blockchain experience.
• Deep understanding of modern machine learning techniques and algorithms including GBM, XGBoost, LGBM, etc.; advanced programming skills in 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.
• Ability and willingness to travel as needed.
• Strong communication skills 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.).

• 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 dependents.
• More benefits we love to share during the process.

The salary range for this position is $ to $. The salary offered depends on a variety of factors, including job‑related knowledge, skills, experience, and market location. In addition to the salary, a performance bonus and long‑term incentives may be provided as part of the compensation package, as well as a full range of medical, financial, and/or other benefits, dependent on the position offered.

Applicants should apply via Okcoin and OKX internal or external careers site.

OKX is committed to equal employment opportunities regardless of race, color, genetic information, creed, religion, sex, sexual orientation, gender identity, lawful alien status, national origin, age, marital status, and non‑job related physical or mental disability, or protected veteran status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.