Data Scientist: Recommendations & Web3 Community (Remote)

Blockchain Academics; Singapore; On-site; SGD 38,000 - 62,000; Full time

Benefits offered by this job

Remote-first

Global exposure

Career growth opportunities

Competitive salary

Job summary

Binance Square is seeking a Data Scientist at an early career level to help build next-generation recommendation and community intelligence systems. You will collaborate with data scientists, engineers, product managers, and business teams to improve content distribution and user engagement.

You will analyze user behavior, experiment with recall/ranking strategies, and apply ML methods, including potential use of LLMs and multimodal models, to drive data-driven improvements across the platform.

Qualifications

• Bachelor’s/Master’s/PhD in CS/Data Science/Statistics or related field.
• Strong analytical skills with solid understanding of statistics and ML.
• Proficient in SQL and Python.
• Familiar with recommendation systems and A/B testing.

Responsibilities

• Analyze user behavior and content quality to improve recommendations.
• Support optimization of recall, ranking, and personalization strategies.
• Build metrics for content quality, user profiling, and community health.
• Collaborate with data scientists, engineers, and product managers to implement data-driven improvements.
• Conduct experiments and monitor metrics to measure impact.

Skills

SQL

Python

Statistics

Machine Learning

Data Mining

A/B Testing

Communication Skills

Crypto Interest

Education

BSc/MSc/PhD in CS/Data Science/Statistics

Job description

Binance Square is seeking a Data Scientist at an early career level to help build next-generation recommendation and community intelligence systems. You will collaborate with data scientists, engineers, product managers, and business teams to improve content distribution and user engagement.

You will analyze user behavior, experiment with recall/ranking strategies, and apply ML methods, including potential use of LLMs and multimodal models, to drive data-driven improvements across the platform.