Binance

Data Scientist, Market Growth Lifecycle

Binance

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Job Level

Mid-LevelSenior

Tech Stack

HadoopJavaPythonPyTorchScalaSparkSQLTensorflowWeb3

About the role

  • 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.

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.