Binance Accelerator Program - Data Scientist (User Growth)
Binance · Remote · mid
Binance · Remote · mid
Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. Binance is trusted by more than 320 million people in 100+ countries for its industry-leading security, transparency, trading engine speed, protections for investors, and unmatched portfolio of digital asset products and offerings from trading and finance to education, research, social good, payments, institutional services, and Web3 features. Binance is devoted to building an inclusive crypto ecosystem to increase the freedom of money and financial access for people around the world with crypto as the fundamental means.
Binance Accelerator Program (BAP) is a 3-6 month internship program designed for Early Career talent to have firsthand experience in the rapidly expanding digital assets space. You will be given the opportunity to develop your skills at Binance and understand what it’s like to work at the world's leading blockchain ecosystem. As part of your internship in the BAP, there will also be opportunities for networking and development, which will expand your professional network and build transferable skills to propel you forward in your career. Learn about the BAP Program HERE.
Current university students and recent graduates.
*Terms of employment / engagement shall be subject to contract and local applicable laws
• Participate in the design and development of algorithm strategies for user growth, including but not limited to user segmentation, intelligent recommendation, and incentive strategy optimization.
• Build user lifecycle models (LTV prediction, churn warning, conversion prediction, etc.) based on user behavior data to drive precision operations and decision-making.
• Design and implement A/B testing experiments to evaluate the effectiveness of growth strategies and drive continuous iteration and optimization.
• Explore user characteristics and behavioral patterns using machine learning and causal inference methods to improve user retention and conversion.
• Collaborate closely with product, operations, and engineering teams to translate algorithmic capabilities into measurable business growth outcomes.
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