Remote Data Scientist Risk Analytics & ML

Binance; Dubai; Remote; AED 50,000 - 73,000; Full time

Benefits offered by this job

Remote-first

Competitive salary

Global team

Job summary

Binance is seeking a motivated student to join the Risk AI DS team in Dubai. You will own end-to-end project streams such as syndicate detection and market manipulation detection, and work with large-scale data.

You will analyze billions of records with PySpark, Hive, and Trino, build SQL pipelines, and develop ML models to improve detection metrics for real-world financial safety and fraud prevention.

Qualifications

• Currently pursuing a degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• Strong foundation in machine learning concepts, with proficiency in Python and SQL.
• Familiarity with database management systems such as MySQL, PostgreSQL, SQL Server, or MongoDB.
• Comfortable working with large-scale datasets; experience with Apache Spark is a plus.
• Proficient in leveraging AI coding agents, such as Claude Code or Cursor, to accelerate development and improve productivity.

Responsibilities

• Own a real-world project stream end-to-end, such as syndicate detection, user behavior sequencing, market manipulation detection, or feature discovery.
• Process and analyze billions of records using PySpark, Hive, and Trino, and develop robust SQL pipelines for feature engineering and validation.
• Build, evaluate, and iterate on machine learning models, translating model performance into meaningful business metrics such as detection rate, false-positive rate, and latency.

Skills

Python

SQL

ML fundamentals

Big data

Data analysis

Education

Bachelor's or current degree in CS/DS/Math/Engineering

Tools

MySQL

PostgreSQL

SQL Server

MongoDB

Apache Spark

Job description

Binance is seeking a motivated student to join the Risk AI DS team in Dubai. You will own end-to-end project streams such as syndicate detection and market manipulation detection, and work with large-scale data.

You will analyze billions of records with PySpark, Hive, and Trino, build SQL pipelines, and develop ML models to improve detection metrics for real-world financial safety and fraud prevention.