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Binance offers a growth-focused internship where you’ll design algorithmic strategies for user acquisition, retention, and engagement. You will build predictive models using ML techniques and collaborate with product and engineering to drive measurable business outcomes.
We seek Master’s or PhD candidates in CS/Statistics/Math/AI, skilled in Python, SQL, and ML; familiarity with recommender systems or causal inference is a plus. Remote-friendly, Singapore-based internship with flexible hours.
Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ 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, and more. Our mission is to increase the freedom of money and financial access for people around the world.
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.
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.
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.
Binance is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success.
By submitting a job application, you confirm that you have read and agree to our Candidate Privacy Notice.
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 is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success.
By submitting a job application, you acknowledge that you have read our Candidate Privacy Notice.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. 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.