Data Scientist, Market Growth Lifecycle

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.