Sr Data Scientist, Risk Strategy
Company websiteokx.com (OKX, opens in new tab)
Base salary $223,661 to $268,333
Employer-published annual base salary, USD. Advertised base range in San Jose, CA
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationSan Jose, CA
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (3 h ago) · observed since
About this job
Who We Are
At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom.
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:
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:
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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
What We Look For In You:
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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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4+ years of fraud analytics experience in financial services or FinTechs
- Crypto/Blockchain experience
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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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Strong communicator in both writing and speaking
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Multi-tasking and strong project management skills
Nice to Haves:
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Hands-on experience/knowledge of modeling in machine learning (GBM, XGBoost, Random Forest, etc.); and
Perks & Benefits
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Competitive total compensation package
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L&D programs and Education subsidy for employees' growth and development
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Various team building programs and company events
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Wellness and meal allowances
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Comprehensive healthcare schemes for employees and dependants
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More that we love to tell you along the process!
OKX Statement:
The salary range for this position is $223,661.00 to $268,333.00. 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.
#LI-HYBRID#LI-ED1
Notice:
All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website.
Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX's Candidate Privacy Notice.
Source: OKX on Greenhouse · View original posting (opens in new tab)
Pay in context
This role's base floor ($223,661) is above 72% of the 1,503 Data & ML roles in California listed on this site. Their median floor is $187,000; the middle half runs from $158,941 to $229,900.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 7, 2026.
This listingSr Data Scientist, Risk Strategy$223,661 to $268,333
Senior/Staff Software Engineer, Mobile Trading$223,611 to $321,999
Sr Product Manager, Risk Platform$223,333 to $268,333
Principal Product Manager, Growth$214,666 to $375,666
Staff Engineer, Machine Learning & Data Infrastructure$214,666 to $321,999
Principal/Senior Product Manager, Payment$214,666 to $321,999
Staff Cloud Infrastructure Engineer$214,666 to $321,999
Chart as a table
| Role | Published base |
|---|---|
| Sr Data Scientist, Risk Strategy (this listing) | $223,661 - $268,333 |
| Senior/Staff Software Engineer, Mobile Trading | $223,611 - $321,999 |
| Sr Product Manager, Risk Platform | $223,333 - $268,333 |
| Principal Product Manager, Growth | $214,666 - $375,666 |
| Staff Engineer, Machine Learning & Data Infrastructure | $214,666 - $321,999 |
| Principal/Senior Product Manager, Payment | $214,666 - $321,999 |
| Staff Cloud Infrastructure Engineer | $214,666 - $321,999 |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2025-12-10
Where this pay comes from
Location as the employer wrote it: San Jose, California, United States
The salary range for this position is $223,661.00 to $268,333.00. The salary offered depends on a variety of factors, includ
- Method
- Employer text, read with fixed rules and re-verified
- Checked
- Rule set
- us-base-v2
The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
