Senior Fraud Detection & Transaction Analytics Lead

Senior Fraud Detection & Transaction Analytics Lead

Full-Time 60000 - 80000 Β£ / year (est.) No working from home possible
Mews

At a Glance

  • Tasks: Use data to enhance fraud detection and reduce false positives in a dynamic environment.
  • Company: Join Mews, a leading fintech company focused on innovation and impact.
  • Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
  • Other info: Be part of a collaborative team dedicated to tackling financial crime.
  • Why this job: Make a real difference in fraud prevention while working with cutting-edge technology.
  • Qualifications: Experience in data analysis, SQL, and Python is essential.

The predicted salary is between 60000 - 80000 Β£ per year.

Mews is hiring a Senior Transaction Monitoring Fraud Data Analyst to join the FinCrime team within Mews Fintech. This is a high-impact data role β€” not a reporting function β€” for someone who can use data to improve fraud detection, reduce false positives, and help the team focus on the cases that carry real risk.

You will work at the intersection of fraud operations, data, and product, using SQL and Python to identify patterns, improve detection rules, and inform better decisions.

Senior Fraud Detection & Transaction Analytics Lead employer: Mews

At Mews, we pride ourselves on being an exceptional employer that fosters a culture of innovation and collaboration. Our team is made up of passionate individuals who are empowered to make impactful decisions, ensuring that every employee has the opportunity for personal and professional growth. Located in a vibrant industry, we offer unique advantages such as autonomy in your role, a commitment to meaningful work, and the chance to shape the future of hospitality technology.

Mews

Contact Details:

Mews Recruitment Team

We think you need these skills to ace Senior Fraud Detection & Transaction Analytics Lead

Fraud Detection
Transaction Analytics
Data Analysis
SQL
Python
Pattern Recognition
Detection Rules Improvement