Data Scientist, Risk
Who We Are:
Okcoin is one of the world’s largest and fastest growing cryptocurrency exchanges. We help millions of people buy and sell bitcoin, and...
Who We Are:
Okcoin is one of the world’s largest and fastest growing cryptocurrency exchanges. We help millions of people buy and sell bitcoin, and other crypto assets every day — but our work is a whole lot more than that. We’re building an inclusive future of finance, one that opens new opportunities to learn financial literacy, store value, and build wealth for everyone.
Ready to help the next billion people experience the future of finance with us? Come on board. We have offices in San Francisco, Malta, Hong Kong, Singapore, Dublin, Austin and San Jose!
About the Team:
The Risk function at Okcoin is responsible for the overall risk and fraud prevention culture at the company. We’re a team of risk-minded problem solvers who advise the business on the company’s regulatory obligations and enterprise risk. We’re also deeply committed to moving the needle on risk standards for the crypto industry, building products in a compliant way, and protecting the company from financial, regulatory and reputational risks. Our team consists of seasoned risk professionals who are based across our global offices.
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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.
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Serve as technical SME by sharing new data mining techniques, maintaining technical reference documentation, and interfacing with partner technology teams.
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Collaborate across business and technology stakeholders to communicate analytical findings to both technical and non-technical audiences.
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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.
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Link Analysis/Graph analytics to find and mitigate deeply-connected fraud networks and detect new accounts being added to these networks
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Unsupervised learning methods to augment existing supervised models, or detect portfolio anomalies
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Development of machine learning models
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Partner with product and engineering team in implementing features and models, and enhancing systems
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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.
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2-3 years of fraud analytics experience in financial services or FinTechs
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Deep understanding of modern machine learning techniques / algorithms including GBM, XGBoost, LGBM, etc. Advanced programming skills of statistical / analytical software (SQL, R, Python,etc.);
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Successful track record of owning and driving large, complex data analysis projects.
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Demonstrated capacity for innovation and outside-the-box thinking in the creation of new capabilities and processes that are unstructured or exploratory in nature.
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Experience in a fast-paced startup environment with a strong level of initiative; and
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Ability and willingness to travel as needed.
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Crypto/Blockchain experience;
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Hands-on experience/knowledge of modeling in machine learning (GBM, XGBoost, Random Forest, etc.); and
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Market competitive total compensation package
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Comprehensive insurance package including medical, dental, vision, disability & life insurance (Company pays 100% for employee/80% for dependents)
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401K with company contribution
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Flexible PTO policy, company paid holidays, and flexible hours
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UberEats Program
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Paid Parental Leave
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Employee Referral Bonus Program paid in BTC
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Company Donation Match
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More surprises when you join!
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