About the role

You will design and develop algorithmic strategies for user growth, including user segmentation and intelligent recommendation systems. Additionally, you will build user lifecycle models and conduct A/B testing to evaluate strategy effectiveness and drive business growth.

What they look for

Python Machine learning SQL NumPy Pandas Scikit-learn User segmentation Intelligent recommendation A/B testing Causal inference Data analysis User lifecycle modeling Recommender systems Reinforcement learning Operations research Optimization

Requirements

Candidates must be currently pursuing a Master's or Ph.D. degree in a quantitative field and be available to intern at least 4 days per week. Proficiency in Python, SQL, and machine learning models is required, along with strong analytical and problem-solving skills.

Benefits

Competitive salary Company benefits Work-from-home arrangement

Full description

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.

About Binance Accelerator Program

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.

Who may apply

Current university students and recent graduates.

*Terms of employment / engagement shall be subject to contract and local applicable laws

\n

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.

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.

\nWhy 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)