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Are you looking to be a part of the most influential company in the blockchain industry and contribute to the crypto-currency revolution that is changing the world?
We have partnered with a global blockchain company behind the world's largest digital asset exchange by trading volume and users, serving a greater mission to accelerate cryptocurrency adoption.
With this, they're looking to expand their Data Science teams and add two Data Scientists to join them on a fully remote basis.
If you were to be successful, you could be based anywhere out of Europe.
In this role, you will have the opportunity to leverage rich data and state-of-art machine learning infrastructure to develop data products that are used by tens of millions of crypto-currency users across the globe, whilst collaborating with a strong team of engineers, data analysts, and business operations to define and build solutions, features, algorithms, and products based on their rich data and cutting-edge machine learning technology.
- Universe risk management: data analysis and modelling to KYC, payment, credit, exchange scenes
- User behaviour and pattern analysis: leverage our PB-scale data warehouse to perform in-depth analysis to build personalized services and provide abnormal user automated recognition
- Digital data asset: obtain the blockchain-based data to perform chain-based data analysis, prediction, and recommendations
- Data-driven customer feedback and satisfaction analysis: leverage machine learning techniques to understand customer's feedback and satisfaction with proven data evidence and analysis
- 4+ years of experience developing machine learning models at scale from inception to business impact
- Deep understanding of modern machine learning techniques and mathematical underpinning, such as classifications, recommendation systems, optimization etc.
- Working with data sizes from Terabyte to Petabyte scale
- Good experience with Python, Java, and/or Scala is preferred (2+ years) with solid project experience
- Experience in Deep Learning is highly desirable