Senior P2P Risk Strategy Analyst

About the job
Established in 2018, the company is one of the world’s leading cryptocurrency exchanges and digital financial platforms, serving over 80 million users across more than 200 countries and regions. Powered by world-class technology and a user-first mindset, the company delivers a seamless ecosystem across trading, payments, wealth management, custody, institutional services, and Web3 — connecting users to the future of digital finance.

Our core values define how we build. We listen, care and improve to create products and experiences that put users first. Backed by a global team of ambitious builders, problem-solvers, and innovators, we foster a high-performance and fast-moving environment where talent is empowered to drive real impact at the global scale. Supported by 24/7 multilingual customer service and a strong commitment to innovation, we are shaping the future of finance through technology, collaboration, and bold execution.

Today, the company is recognized as one of the most trusted and transparent platforms in the digital asset industry, continuing to expand its global presence while building the infrastructure for the next generation of financial services.

Position Overview
We are seeking a highly analytical and data-driven P2P Risk Strategy Specialist to design, optimize, and scale our risk automation framework. In this role, you will be responsible for protecting our platform against peer-to-peer transaction risks, including account takeovers, social engineering scams, money laundering, and payment velocity abuse.

You will combine a strong Data background with hands-on coding in Python and SQL to detect subtle fraud patterns across massive transaction ecosystems.

Key Responsibilities

• Pattern Detection & Behavioral Analysis: Mine high-volume, multi-dimensional transaction and event logs to uncover emerging P2P fraud vectors, synthetic networks, collusion rings, and anomalous transfer patterns.
• Risk Strategy Development: Design, implement, and iterate real-time decisioning rules and risk policies (e.g., dynamic transfer limits, step-up authentication, cooling-off periods) to mitigate risk while preserving a frictionless user experience.
• Advanced Data Analysis: Write production-grade, optimized SQL and Python scripts to analyze network graphs, transaction velocity, device signals, and user interaction metrics.
• Model Integration & Experimentation: Translate models into operational strategies, establish decision thresholds, and run A/B tests to quantify strategy performance.
• Post-Mortem & Loss Mitigation: Perform quantitative root-cause analysis on fraudulent transactions, chargebacks, and ATO incidents to plug strategy gaps and minimize direct financial losses.
• Risk Performance Monitoring: Build and maintain automated dashboards and KPI tracking systems.

Qualifications & Requirements
Core Requirements:

• 3+ years of experience in risk strategy, transaction monitoring, payment fraud analysis, or trust & safety within Fintech, Banking, or Digital Marketplaces.
• Advanced SQL Skills: Proficient in complex joins, window functions, CTEs, and optimizing queries on large-scale distributed databases (e.g., Snowflake, BigQuery, Redshift).
• Proficient in Python: Strong experience using Python libraries (pandas, numpy, scikit-learn, networkx) for data manipulation, exploratory data analysis, and rule automation.
• Pattern Detection & Analytics: Proven track record of identifying complex fraud networks, transaction velocity anomalies, or multi-account abuse patterns.

Preferred Experience & Education:

• Educational Background: Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, Economics, or a related quantitative field (Data Science background strongly preferred).
• Direct experience with P2P payment mechanisms, real-time settlement rails, card-to-card transfers, or digital wallets.
• Hands-on experience with graph theory/network analysis (identifying linked accounts, shared device fingerprints, IP linkages).
• Familiarity with machine learning workflows, rule engine architectures, and dynamic risk-scoring frameworks.
• Strategic Problem Solver: Comfortable tackling ambiguous, rapidly evolving risk problems in a fast-paced environment.
• Cross-Functional Communication: Excellent at translating data science insights and technical risk concepts into strategic recommendations for business stakeholders.

Why Join Us
At the company, we are committed to fostering a supportive and enriching work environment.
Our benefits include:

• Study Growth Fund: We support your professional development and continuous learning.
• Internal Events: Participate in regular team-building activities, workshops, and events designed to promote collaboration and innovation.
• Global Collaboration: Be part of a diverse, international team, working alongside colleagues from around the world.
• Career Advancement: Access opportunities for growth and advancement within a rapidly expanding global company.
• Internal Mobility: Grow with us- Your long-term development is important to us. We offer internal job opportunities to help build your career path.