Data Scientist - Recommendations & Community (Remote)

Binance; Singapore; Remote; SGD 60,000 - 90,000; Full time

Benefits offered by this job

Remote-first

Competitive salary

Career growth

Learning opportunities

Job summary

Binance is seeking an early-career Data Scientist to join the Binance Square team. You will help develop next-generation recommendation and community intelligence systems, working with scientists, engineers, product managers, and business teams to improve content distribution and user engagement.

You will explore recall and ranking strategies, design experiments, and apply ML and data mining techniques to optimize content and creator discovery in a fast-paced, global environment.

Qualifications

• Pursuing a degree in CS, Data Science, Statistics, Mathematics, Engineering, or related fields.
• Strong analytical skills with solid understanding of statistics and ML.
• Proficient in SQL and at least one programming language such as Python.
• Familiar with recommendation systems, ranking models, or A/B testing is a plus.

Responsibilities

• Analyze user behavior, content quality, creator performance, and feed patterns.
• Support optimization of recall, ranking, cold-start, diversity, and personalization.
• Build metrics for content quality, user profiling, and community health.
• Conduct A/B testing, monitor metrics, and perform deep dives on results.
• Explore LLMs and multimodal models for content understanding and distribution.
• Collaborate with data engineers to improve pipelines and experiment tracking.

Skills

Python

SQL

Statistics

Machine learning

Data mining

Problem solving

Communication

Education

Bachelor's/Master's/PhD in CS/Data Science/Statistics/Math/Engineering

Tools

Python

SQL

Job description

Binance is seeking an early-career Data Scientist to join the Binance Square team. You will help develop next-generation recommendation and community intelligence systems, working with scientists, engineers, product managers, and business teams to improve content distribution and user engagement.

You will explore recall and ranking strategies, design experiments, and apply ML and data mining techniques to optimize content and creator discovery in a fast-paced, global environment.