Bybit — one of the world’s leading cryptocurrency exchanges and digital financial platforms, established in 2018 and now serving over 80 million users across 200+ countries, offering trading, payments, wealth management, custody, institutional services, and Web3 — is seeking a highly analytical and data-driven Senior P2P Risk Strategy Analyst in Abu Dhabi. This high-impact role designs, optimises, and scales the risk automation framework that protects Bybit’s peer-to-peer transaction ecosystem against account takeovers, social engineering scams, money laundering, and payment velocity abuse — combining a strong data analytics background with production-grade Python and SQL to detect subtle fraud patterns across massive P2P transaction ecosystems at global scale.
About Bybit — Building the Future of Digital Finance
Company: Bybit — one of the world’s leading cryptocurrency exchanges, serving 80M+ users across 200+ countries with trading, payments, wealth management, custody, institutional services, and Web3
Recognition: One of the most trusted and transparent platforms in the digital asset industry — with a strong commitment to innovation, user-first product development, and responsible platform governance
P2P Risk Context: The P2P Risk Strategy team protects Bybit’s peer-to-peer transaction ecosystem from account takeovers, synthetic fraud networks, money laundering, social engineering scams, and payment velocity abuse at massive global scale
Culture: High-performance, fast-moving, ambitious builder culture — talent empowered to drive real impact at global scale with 24/7 multilingual customer service and bold execution
Why This Senior P2P Risk Strategy Analyst Role Stands Out
80M User Scale — Real Impact: Protect one of the world’s largest crypto exchange P2P ecosystems — with fraud pattern detection, risk strategy design, and automation work that directly affects platform integrity and user protection at genuinely global scale
Full Technical Ownership: Pattern detection, risk strategy development, model integration, A/B testing, post-mortem analysis, and performance monitoring — comprehensive end-to-end P2P risk strategy ownership in a single senior role
Graph & Network Analysis Frontier: Apply networkx and graph theory to identify synthetic fraud networks, linked accounts, shared device fingerprints, and collusion rings — one of the most technically sophisticated applications of data science in financial crime detection
Crypto Industry Leadership: Work at a globally recognised digital asset exchange in Abu Dhabi’s growing digital finance hub — contributing to the risk infrastructure of one of the world’s top cryptocurrency platforms
Position Overview
This Senior P2P Risk Strategy Analyst at Bybit in Abu Dhabi mines high-volume, multi-dimensional transaction and event logs to uncover emerging P2P fraud vectors, synthetic networks, collusion rings, and anomalous transfer patterns — designing, implementing, and iterating real-time decisioning rules and risk policies including dynamic transfer limits, step-up authentication, and cooling-off periods. The role writes production-grade Python and SQL scripts to analyse network graphs, transaction velocity, device signals, and user interaction metrics — translating ML models into operational strategies, running A/B tests, performing quantitative root-cause analysis on fraudulent transactions and ATOs, and building and maintaining automated dashboards and KPI tracking systems that monitor P2P risk performance across Bybit’s global platform.
Why This Role Matters: As Senior P2P Risk Strategy Analyst at Bybit in Abu Dhabi, you are the analytical intelligence layer that stands between Bybit’s 80 million users and the fraud actors who attempt to exploit them through the P2P transaction ecosystem every day. When your graph analysis correctly maps a synthetic fraud network of 47 linked accounts that share device fingerprints and IP clusters before they successfully launder funds through Bybit’s platform, your transaction velocity rule detects a payment abuse pattern two hours into a new attack campaign and automatically applies a cooling-off period that stops the losses before they compound, or your A/B test proves that a step-up authentication trigger reduces account takeover success rates by 60% without materially increasing friction for legitimate users — you are not performing risk analytics. You are protecting the financial integrity and user trust of one of the world’s leading cryptocurrency exchanges at a scale that makes every basis point of improvement meaningful.
Key Responsibilities
Pattern Detection, Fraud Network Analysis & Behavioural Mining
- Mine high-volume, multi-dimensional P2P transaction and event logs to uncover emerging fraud vectors — applying advanced SQL queries, Python data manipulation, and network graph analysis to detect synthetic fraud networks, collusion rings, shared device fingerprint clusters, and anomalous transfer patterns across Bybit’s global P2P ecosystem
- Apply networkx and graph theory to identify linked accounts, IP linkages, shared device fingerprints, and coordinated multi-account fraud behaviour — building graph-based detection frameworks that surface hidden fraud network structures invisible to individual transaction-level analysis
- Track transaction velocity anomalies, payment pattern deviations, and user interaction irregularities — building behavioural analytics that detect account takeover attempts, social engineering scam patterns, and money laundering flows in real time
Risk Strategy Development, Rule Design & Policy Implementation
- Design, implement, and iterate real-time P2P risk decisioning rules and risk policies — including dynamic transfer limits, step-up authentication triggers, cooling-off periods, and transaction suspension logic — balancing fraud loss reduction with minimal friction for legitimate users
- Translate ML models into operational risk strategies — establishing decision thresholds, implementing model outputs in rule engine architecture, and running A/B tests to quantify the performance impact of strategy changes against both fraud reduction and user experience metrics
- Propose and implement new risk policy innovations in response to emerging fraud vectors — demonstrating the ability to tackle ambiguous, rapidly evolving P2P fraud problems in Bybit’s fast-paced global platform environment
Post-Mortem Analysis, Loss Mitigation & Performance Monitoring
- Perform quantitative root-cause analysis on fraudulent P2P transactions, chargebacks, and account takeover incidents — identifying the strategy gaps, rule failures, and detection blind spots that allowed losses to occur and implementing automated safeguards to prevent repeats
- Build and maintain automated risk performance dashboards and KPI tracking systems — providing real-time visibility into P2P fraud rates, strategy effectiveness, override patterns, and loss metrics across Bybit’s global P2P transaction ecosystem
- Translate data science insights and technical risk findings into clear strategic recommendations for business stakeholders — communicating complex fraud pattern analysis in a manner that drives prompt, informed risk policy decision-making across the organisation
Qualifications & Experience
Essential 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 optimising queries on large-scale distributed databases including Snowflake, BigQuery, or Redshift
- Proficient Python — strong experience with Python libraries (pandas, numpy, scikit-learn, networkx) for data manipulation, exploratory data analysis, and rule automation
- Proven track record of identifying complex fraud networks, transaction velocity anomalies, or multi-account abuse patterns in high-volume digital payment or crypto environments
Preferred Experience
- 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 in a crypto, fintech, or digital marketplace context
- Hands-on experience with graph theory and network analysis — identifying linked accounts, shared device fingerprints, and IP linkage patterns in large-scale transaction datasets
- Familiarity with machine learning workflows, rule engine architectures, and dynamic risk-scoring frameworks in production fraud detection environments
About Bybit — Digital Finance for 80 Million Users Worldwide
Established in 2018, Bybit 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 with trading, payments, wealth management, custody, institutional services, and Web3. Recognised as one of the most trusted and transparent platforms in the digital asset industry, Bybit is powered by world-class technology and a user-first mindset — backed by a global team of ambitious builders, problem-solvers, and innovators in a high-performance environment where talent drives real impact at global scale. As Senior P2P Risk Strategy Analyst in Abu Dhabi, you build the analytical infrastructure that keeps Bybit’s peer-to-peer ecosystem safe and trusted for the millions of users who depend on it every day.
Career Excellence: Detect P2P fraud networks, design risk strategies, and protect 80M+ Bybit users — Python, SQL, graph analysis, Abu Dhabi UAE.
Who Should Apply?
- P2P Fraud & Transaction Monitoring Analysts — Crypto/Fintech: With 3+ years of P2P fraud detection, transaction monitoring, or risk strategy experience — applying advanced SQL and Python to identify fraud networks and velocity anomalies in high-volume digital payment ecosystems
- Graph Theory & Network Analysis Specialists — Fraud: With hands-on networkx or equivalent graph analysis experience — mapping linked accounts, device fingerprint clusters, and IP linkage patterns to surface synthetic fraud networks in P2P transaction data
- Risk Rule Engine & Strategy Designers: With experience designing, implementing, and A/B testing real-time risk decisioning rules — balancing fraud loss reduction with user experience preservation in consumer-facing digital financial platforms
- Python & SQL Data Scientists — Financial Crime: With production-grade Python (pandas, scikit-learn) and advanced SQL (window functions, CTEs, distributed databases) applied to fraud detection, AML monitoring, or trust and safety analytics at scale
- Abu Dhabi-Based Digital Asset Risk Professionals: Seeking a senior analytical role at one of the world’s top 3 cryptocurrency exchanges — contributing to the fraud detection and risk strategy infrastructure that protects 80M+ users globally from Abu Dhabi
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