Senior Risk Strategy Analyst

Job description

Bybit is looking for a highly analytical Risk Strategy Analyst in Abu Dhabi to design, optimise and scale its risk automation framework. The role protects the platform against peer-to-peer transaction risks such as account takeovers, social engineering scams, money laundering and payment velocity abuse.

The analyst combines a strong data background with hands-on SQL and Python to detect fraud patterns across large transaction volumes, builds real-time decisioning rules, runs experiments to measure strategy performance, and maintains dashboards and KPI tracking.

Responsibilities

• Pattern Detection & Behavioral Analysis: Mine high-volume, multi-dimensional transaction and event logs to uncover emerging 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

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.
• 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 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.

Skills

• Fraud Detection
• Network Analysis
• Python
• Risk Strategy
• SQL
• Transaction Monitoring