Senior Data Analyst: Trading Insights & ML (Remote)

Binance; Hong Kong; Hybrid; HKD 600,000 - 900,000; Full time

Benefits offered by this job

Work-from-home arrangement

Job summary

Binance is seeking a data analytics professional to support the Trading Business Unit. You will collaborate with trading, operations and product teams to transform large-scale data into actionable insights that inform fast, high-stakes decisions.

Responsibilities include building visualizations, models and experiments, interpreting PB-scale data, and presenting clear recommendations to executives and cross-functional teams, with time-to-market as a priority.

Qualifications

• Degree in a quantitative discipline (Math/Statistics/CS/Engineering/Life Sciences).
• At least 3 years in Analytics or Data Science.
• Self-driven team player with ability to learn new tools and techniques.
• Curiosity to identify trends and explain data clearly.
• Internal consulting/business transformation experience preferred.
• Interest in Emerging Technologies related to Blockchain, ML and AI.

Responsibilities

• Work across data spectrum from engineering to visualisations, ML models and experiments for the Trading business.
• Analyze PB-scale transaction, operations and customer data with proprietary and open-source tools.
• Translate complex findings into simple visualisations and actionable recommendations for trading, operations and executives.
• Be part of a fast-paced environment where time to market is critical.

Skills

R/SAS

Python/Java/C++

Tableau/PowerBI

SQL/NoSQL/Neo4J

Education

Quantitative degree

Tools

Tableau

PowerBI

SQL

Job description

Binance is seeking a data analytics professional to support the Trading Business Unit. You will collaborate with trading, operations and product teams to transform large-scale data into actionable insights that inform fast, high-stakes decisions.

Responsibilities include building visualizations, models and experiments, interpreting PB-scale data, and presenting clear recommendations to executives and cross-functional teams, with time-to-market as a priority.