Responsibilities:
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.
Requirements:
Currently pursuing a Master's or Ph.D. degree in Computer Science, Statistics, Mathematics, Artificial Intelligence, or a related field. Available to intern for at least 4 days per week, with a minimum internship duration of 3 months.
Solid foundation in machine learning, familiar with common models (e.g., LR, GBDT, DNN) and their applicable scenarios.
Proficient in Python, with hands-on experience using NumPy, Pandas, and Scikit-learn for data analysis and modeling.
Strong SQL skills, able to independently extract and analyze data from databases.
Familiarity with at least one of the following areas is preferred: recommender systems, causal inference, reinforcement learning, or operations research/optimization.
Prior internship or project experience in user growth, computational advertising, search/recommendation systems is a plus.
Strong communication skills and self-motivation, with the ability to learn quickly and solve problems independently.
Nice-to-Haves
Experience in data science competitions (e.g., Kaggle, Tianchi) with notable achievements.
Familiarity with growth-specific methods such as Uplift Modeling and Multi-Armed Bandit.
Experience with large-scale data processing frameworks (e.g., Spark, Flink).
Publications in machine learning, data mining, or related fields.
Why Binance
• Shape the future with the world’s leading blockchain ecosystem
• Collaborate with world-class talent in a user-centric global organization with a flat structure
• Tackle unique, fast-paced projects with autonomy in an innovative environment
• Thrive in a results-driven workplace with opportunities for career growth and continuous learning
• Competitive salary and company benefits
• Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)
Binance is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success.
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Binance Melbourne, Victoria, AUS Office
Melbourne, VIC, Australia
