Fraud Data Analyst

About the role

The Fraud Data Analyst will design, develop, and maintain predictive models and machine‑learning algorithms that detect suspicious activities across our platforms. You will work closely with risk, compliance, and IT teams to turn data into actionable insights that protect the business and its customers.

Key responsibilities

• Develop and deploy fraud detection models using advanced analytics and machine‑learning techniques.
• Continuously improve fraud monitoring systems to increase detection accuracy and reduce false positives.
• Analyze internal and external data sources to uncover vulnerabilities and recommend proactive controls.
• Define, track, and report on KPIs that measure the effectiveness of fraud‑prevention strategies.
• Stay current on emerging fraud tactics, industry benchmarks, and regulatory changes.
• Lead a multidisciplinary team of analysts, data scientists, and market‑intelligence specialists.
• Collaborate with risk management, compliance, IT, and other stakeholders to ensure alignment and clear communication.

Required profile

• Master’s degree in Data Science, Statistics, Economics, Business Administration, or a related field.
• 10+ years of experience in fraud analytics, risk management, or data analytics.
• Proven track record of building and implementing fraud detection systems.
• Strong analytical, problem‑solving, and strategic thinking abilities.
• Excellent leadership, team‑building, and communication skills.

Required skills

• Python
• R
• SQL
• SAS
• Machine‑learning platforms and fraud‑detection software