Senior P2P Risk Strategy Analyst

About the Role
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.