Data Scientist/Machine Learning Engineer

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 280 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 The Role
In this role, you will be responsible for developing and optimising core algorithmic models in marketing scenarios, including user behaviour prediction, profiling, ROI estimation, and traffic allocation strategies. You will design and build precision marketing models such as CTR/CVR prediction, LTV forecasting, and channel attribution analysis, leveraging user profiles, real-time behavioural data, and business objectives. A key part of the role will be creating data-driven strategies for user acquisition, retention, and repurchase, while continuously validating and improving performance through A/B testing, causal inference, and attribution analysis. You will collaborate closely with data, product, and operations teams to ensure these algorithms are effectively deployed within Binance's marketing systems to drive measurable growth.

Responsibilities:

• Responsible for core algorithm models in marketing scenarios, including but not limited to user behavior prediction, user profiling, ROI estimation, and traffic allocation strategies, to improve marketing efficiency and conversion rates.
• Build precision marketing models (such as CTR/CVR prediction, LTV forecasting, marketing channel attribution analysis, etc.) based on user profiles, real-time behavioral data, and business objectives.
• Design data-driven algorithm strategies for user lifecycle management (acquisition, retention, repurchase) to optimize user growth and operational performance.
• Deeply understand business needs and continuously track algorithm performance; validate and optimize models through A/B testing, causal inference, and attribution analysis, ensuring ongoing iteration and business impact.
• Collaborate closely with data, product, and operations teams to drive the implementation of algorithms in marketing systems (e.g., user growth initiatives).

Requirements:

• At least 3 years of experience in related fields, with a solid foundation in algorithms and programming.
• Master's Degree or above in Computer Science, Statistics, Applied Mathematics, Machine Learning, or related disciplines.
• Proficient in at least one programming language such as Python, Scala, or Java; familiar with big data processing frameworks like Hadoop, Spark, or Flink.
• Strong understanding of machine learning algorithms (e.g., LR, GBDT, DNN), commonly used models in marketing scenarios (e.g., Uplift Model, Lookalike), and tools such as TensorFlow or PyTorch.
• Familiar with SQL/Hive and experienced in large-scale data cleaning, feature engineering, and model tuning.
• Deep understanding of user growth, ad placement, and e-commerce marketing scenarios, with the ability to design algorithm solutions aligned with business goals.
• Clear logical thinking, ability to work independently, and strong team collaboration and communication skills.

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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