Description
Binance is the leading global blockchain ecosystem and cryptocurrency infrastructure provider whose suite of financial products includes the world’s largest digital-asset exchange.
Our mission is to accelerate cryptocurrency adoption and increase the freedom of money.
If you’re looking for a fast-paced, mission-driven organization where opportunities to learn and excel are endless, then Binance is the place for you.
Binance is the leading global blockchain ecosystem and cryptocurrency infrastructure provider whose suite of financial products includes the world’s largest digital-asset exchange.
Our mission is to accelerate cryptocurrency adoption and increase the freedom of money.
If you’re looking for a fast-paced, mission-driven organization where opportunities to learn and excel are endless, then Binance is the place for you.
Responsibilities:
Working closely with Fin Crime & Compliance team to improve work efficiency as well as mitigate compliance riskInterpret data and translate statistical insights into actionable decisions to drive operational effectiveness and efficiencyLead the development, maintenance, and definition of specific compliance systems ( such as AML detection engine )Help maintain existing in production models, support audit requests which include : QA testing, and continuous improvement initiatives Identify new business improvement opportunity and lead the end to end development from proof of concept to production deployment
Requirements:
Bachelor's Degree (or above) in quantitative discipline, PHD will be a plus8 years of hands-on experiences as Data Scientist within financial tech, blockchain companies, preferably exposure in onchain analysis. Proficient in python, SQL, with demonstrated experience build & maintain in production ML models use AWS suits Down to earth, willing to take ad-hoc data analysis requests as well as leading end to end development of productsGood tracking of international cutting-edge technology, proficient in reading English documents of international conferences and journals and applying them to engineering practice
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