Sr. Data Scientist, Risk

San Jose, California, United States

Applications have closed

Okcoin

Okcoin is a secure cryptocurrency exchange which makes it easy buy Bitcoin, Ethereum, Dogecoin, and other crypto. Earn crypto rewards with Okcoin earn.

View company page

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 inSan Jose, San Francisco, Austin, Malta, Singapore, Hong Kong, Dublin, and Japan.

 

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.

  About the Opportunity:   This is a highly-impactful role at one of the fastest-growing global cryptocurrency exchanges headquartered in San Francisco, CA. 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 modeling 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 lead key initiatives with integrity and a passion for investigations, problem solving, and troubleshooting.     What You’ll Be Doing:
  • 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
  What We Look For In You:
  • 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
  • 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
  Nice to Haves:
  • Crypto/Blockchain experience;
  • Hands-on experience/knowledge of modeling in machine learning (GBM, XGBoost, Random Forest, etc.); and
  Highlights of Perks and Benefits
  • Market competitive total compensation package
  • Comprehensive insurance package including medical, dental, vision, disability & life insurance (Company pays 100% for employee/80% for dependents)
  • 401K with company contribution
  • Paid Parental Leave
  • Employee Referral Bonus Program paid in BTC
  • Company Donation Match
  • More surprises when you join!
  Okcoin Statement Okcoin 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.

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: APIs Blockchain Computer Science Crypto Data analysis Data Mining Economics Engineering Finance Machine Learning Mathematics ML models PhD Python R Research SQL Statistics XGBoost

Perks/benefits: 401(k) matching Career development Competitive pay Health care Insurance Medical leave Parental leave Salary bonus Startup environment

Region: North America
Country: United States
Job stats:  8  4  0
Category: Data Science Jobs

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.