Fraud Risk & ML Analyst (FinTech)

Glovo Group; Barcelona; Hybrid; EUR 42,000 - 65,000; Full time

Benefits offered by this job

Private health insurance

Monthly Glovo credit

Flexible compensation discounts

Gym memberships

Two days work from home weekly

Work from anywhere up to three weeks a

Job summary

Glovo Group is seeking a Fraud Risk Analyst to identify opportunities to reduce losses, implement end-to-end prevention strategies, and monitor performance across fraud streams. You will collaborate with Product, Engineering, and Data Science to propose preventive controls and analyze patterns with SQL and Python.

With 1–3 years in fraud prevention or analytics and a quantitative degree, you will own risk signals, test frameworks, and executive dashboards in Looker to track OKRs and exposure.

Qualifications

• 1-3 years of experience in fraud prevention, risk management, fintech or analytics.
• Bachelor’s degree in Economics, Statistics, Mathematics, Engineering, or a related quantitative field.
• Strong analytical skills with proficiency in SQL; familiarity with Python or other analytical tools is a plus.
• Experience with BI tools such as Looker, Tableau, or similar.
• Knowledge of Precision vs. Recall, and A/B testing principles.
• Good communication and stakeholder management skills.

Responsibilities

• Identify opportunities to reduce fraud losses and improve profitability using risk rules and ML.
• Implement end-to-end fraud prevention strategies and measure impact.
• Support evaluation of fraud controls via A/B tests and monitoring.
• Collaborate with Product, Engineering, and Data Science to propose preventive controls.
• Perform risk analysis using SQL, Python and analytics platforms to identify patterns.

Skills

SQL

Python

Analytics

Stakeholder mgmt

Looker

English

Education

Bachelor’s degree in Economics/Statistics/Math/Engineering

Tools

Looker

Tableau

BigQuery

Job description

Glovo Group is seeking a Fraud Risk Analyst to identify opportunities to reduce losses, implement end-to-end prevention strategies, and monitor performance across fraud streams. You will collaborate with Product, Engineering, and Data Science to propose preventive controls and analyze patterns with SQL and Python.

With 1–3 years in fraud prevention or analytics and a quantitative degree, you will own risk signals, test frameworks, and executive dashboards in Looker to track OKRs and exposure.