P2P Risk & Fraud Strategy Lead

Bybit; Abu Dhabi; On-site; AED 350,000 - 520,000; Full time

Benefits offered by this job

Growth Fund

Internal Events

Global Collaboration

Career Advancement

Internal Mobility

Job summary

Bybit is seeking a highly analytical P2P Risk Strategy Specialist to design, optimize, and scale our risk automation framework. You will protect the platform from peer-to-peer fraud, including account takeovers and money laundering, while preserving a seamless user experience.

You will combine a strong data background with Python and SQL to detect fraud across massive transaction ecosystems, build dashboards, and drive real-time decisioning.

Qualifications

• 3+ years of experience in risk strategy, transaction monitoring, payment fraud analysis, or trust & safety within Fintech, Banking, or Digital Marketplaces.
• Advanced SQL skills: complex joins, window functions, CTEs on large-scale distributed databases.
• Proficient in Python with pandas, numpy, scikit-learn, networkx for data manipulation and rule automation.
• Pattern detection & analytics demonstrating fraud networks or multi-account abuse patterns.

Responsibilities

• Mine high-volume, multi-dimensional logs to uncover P2P fraud vectors and anomalous transfer patterns.
• Design and iterate real-time risk rules and policies to balance security and user experience.
• Write production-grade SQL and Python scripts for graph/network analysis and risk metrics.
• Translate models into operational decisioning, set thresholds, and run A/B tests.
• Perform root-cause analysis on fraud events to minimize losses and improve risk posture.
• Build and maintain automated dashboards and KPI tracking for risk performance.

Skills

SQL

Python

Fraud Analytics

Pattern Detection

Education

Bachelor’s or Master’s in Data Science/CS/Statistics

Tools

Snowflake

BigQuery

Redshift

pandas

networkx

Job description

Bybit is seeking a highly analytical P2P Risk Strategy Specialist to design, optimize, and scale our risk automation framework. You will protect the platform from peer-to-peer fraud, including account takeovers and money laundering, while preserving a seamless user experience.

You will combine a strong data background with Python and SQL to detect fraud across massive transaction ecosystems, build dashboards, and drive real-time decisioning.