Data Analyst, Risk

About the Company

Binance operates a major global blockchain ecosystem and is behind the world’s largest cryptocurrency exchange by trading volume and registered users. The company is used by more than 300 million people across over 100 countries and is known for its security standards, transparency around user funds, trading performance, liquidity, and broad digital-asset offerings. Its products span trading, finance, education, research, payments, institutional solutions, Web3 capabilities, and more. The organization uses blockchain and digital assets to support a more open financial system and improve access to financial services worldwide.

Role Overview

Binance is seeking a detail-focused Data Analyst to strengthen its risk-related analytics work. The role centers on developing and maintaining user tagging frameworks, creating reliable user profiles, and turning large-scale behavioral data into practical insights. You will partner with teams across the business to improve personalization, support risk controls, and help drive decisions with data.

Key Responsibilities

• Oversee and update a robust user-tagging framework that supports personalization efforts and risk management work.
• Study user activity data to build precise, adaptable, and useful user profiles.
• Use data mining, feature engineering, and exploratory analysis to uncover insights from very large datasets.
• Work with Product, Risk, Marketing, and Technology teams to improve segmentation and targeting approaches.
• Track how well tags and profiles perform, and keep improving their quality, accuracy, and relevance.
• Help embed data-led decision-making into everyday business processes.
• Spot behavioral patterns, anomalies, and new trends that can support growth and reduce risk.
• Contribute to better analytical methods, profiling systems, and ongoing process improvements.

Requirements

• A bachelor’s degree or higher in Data Science, Statistics, Computer Science, Mathematics, Economics, or a closely related discipline.
• 3 to 5 years of experience in data analysis, user profiling, customer segmentation, or similar work.
• Strong grounding in analytics, behavioral data interpretation, and segmentation techniques.
• Hands-on ability with Python, SQL, and visualization platforms such as Tableau or Power BI.
• Exposure to big-data environments and related tooling will be an advantage.
• Good understanding of tagging frameworks and user-journey mapping.
• Strong preference for candidates familiar with black-market ecosystems and the operating patterns of bonus abuse, promotion abuse, or fraudulent studio groups; direct experience identifying and countering these activities is highly valued.
• Experience with machine learning methods and applying them to user data is beneficial.
• Strong analytical reasoning and problem-solving capability.
• Comfortable collaborating in a fast-moving, international team setting.
• Very careful with data quality, consistency, and integrity.
• Exposure to AI tools and practical use cases is a plus.

Preferred Background

• Experience in internet platforms, fintech, risk control, growth analytics, or anti-fraud domains.
• Familiarity with experimentation design, A/B testing, and lifecycle analysis.
• Experience handling large behavioral datasets and near real-time analytics use cases.

Why Join Binance

• Contribute to one of the world’s leading blockchain ecosystems.
• Work with top-tier talent in a global, user-focused organization with a flat structure.
• Take ownership of fast-moving, high-impact projects in an innovative setting.
• Enjoy a performance-oriented culture with room to grow and keep learning.
• Receive a competitive salary and company benefits.
• Work-from-home support is available, though the arrangement may differ based on the needs of the business team.

Additional Information

Binance is an equal opportunity employer and values a diverse workforce as essential to its success.

By applying, you acknowledge that you have read and agree to the Candidate Privacy Notice.

The company may use AI tools in parts of the hiring process, such as reviewing applications, analyzing resumes, assessing responses, and checking for possible inconsistencies or verification signals in submitted materials. These tools support the recruitment team but do not replace human judgment. Final hiring decisions are made by people. For more information about how your data is processed, you may contact the company.