Binance Accelerator Program - Data Scientist (TechOps)

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by over 230 million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.

About Binance Accelerator Program Binance Accelerator Program is a concise fixed-term program designed for Early Career Talent to have an immersive experience in the rapidly expanding Web3 space. You will be given the opportunity to experience life at Binance and understand what goes on behind the scenes of the worlds’ leading blockchain ecosystem. Alongside your job, there will also be a focus on networking and development, which will expand your professional network and build transferable skills to propel you forward in your career.

Learn about BAP Program HERE Who may apply Current University students and recent Graduates who can commit at least 6 months tenure, 5 days per week.

Responsibilities:

• Leverage of 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 of machine learning techniques to understand customer’s feedback and satisfaction with proven data evidence and analysis

Requirements:

• Must be a full-time undergraduate/graduate student in good academic standing
• Project experience with developing machine learning models at scale
• Deep understanding of modern machine learning techniques and mathematical underpinning, such as classifications, recommendation systems, optimization and etc
• Good experience with processing large size data is preferred
• Good experience with Python, Java and/or Scala is preferred
• Master’s or above is preferred