Data Scientist Intern: Growth & Personalization

Blockchain Academics; Singapore; Hybrid; SGD 17,000 - 25,000; Part time

Benefits offered by this job

Work-from-home arrangement

Job summary

Binance in Singapore is seeking a growth-focused ML intern to help design algorithmic strategies for user growth and retention. You will work with product, operations, and engineering to translate insights into measurable business outcomes.

You will build lifecycle models (LTV, churn) and run A/B tests, using Python (NumPy, Pandas, scikit-learn) and SQL to analyze large behavioural datasets. Must be pursuing MSc/PhD and commit 3 months, 4 days/week.

Qualifications

• Pursuing a Master’s or PhD in CS/Statistics/Math/AI, 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 models like LR, GBDT, DNN and their use cases.
• Proficient in Python (NumPy, Pandas, Scikit-learn) with data analysis and modeling.
• Strong SQL skills to independently extract and analyze data.

Responsibilities

• Participate in the design and development of algorithm strategies for user growth, including segmentation, recommendations, and incentive strategy optimization.
• Build user lifecycle models (LTV, churn warning, conversion prediction) from behavioural data to drive decisions.
• Design and implement A/B tests to evaluate growth strategies and drive iteration.
• Explore user characteristics using ML and causal inference to improve retention and conversion.
• Collaborate with product, operations, and engineering to translate algorithms into growth outcomes.

Skills

Machine learning

Python

SQL

Data analysis

Communication

Recommender systems

Causal inference

Reinforcement learning

Optimization

Education

Master's or PhD in CS/Statistics/Math/AI

Tools

Python (NumPy, Pandas, Scikit-learn)

Job description

Binance in Singapore is seeking a growth-focused ML intern to help design algorithmic strategies for user growth and retention. You will work with product, operations, and engineering to translate insights into measurable business outcomes.

You will build lifecycle models (LTV, churn) and run A/B tests, using Python (NumPy, Pandas, scikit-learn) and SQL to analyze large behavioural datasets. Must be pursuing MSc/PhD and commit 3 months, 4 days/week.