Fraud Intelligence Data Analyst - Hybrid Role

Riskified; Lisboa; Híbrido; EUR 37 000 - 42 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Hybrid work mode

Wellbeing benefits

Stock-based awards

Resumo da oferta

Riskified is hiring a Data Analyst to join the Fraud Intelligence team in Lisbon. You will research fraud methods, analyze large datasets, and help build detection tools that power our fraud-prevention engine.

You will collaborate with Data Science, Product, and Engineering to translate insights into actionable improvements. The role requires 2–3+ years of analytics with SQL and experience in R or Python, plus strong communication skills in English.

Qualificações

• 2-3+ years of analytical experience with complex data.
• 2+ years of hands-on SQL experience.
• Proven expertise in analysis tools such as R and Python.
• Strong problem-solving and critical thinking skills.
• Ability to manage multiple tasks and lead several projects.
• Fluent written and spoken English; client-facing experience a plus.
• Advantage: fraud, payments, or ecommerce domain knowledge.

Responsabilidades

• Research and investigate new fraud modus operandi (MOs) across our merchant base.
• Analyze large-scale transactional data using SQL (and Python or R) to uncover patterns and trends.
• Collaborate with Data Science, Product, and Engineering to build and refine fraud-detection tools.
• Translate research findings into actionable insights to improve detection accuracy and merchant performance.
• Monitor and evaluate existing detection logic, flag gaps or drift as patterns evolve.
• Document investigation findings and methodologies for the team's knowledge base.
• Work cross-functionally with Risk Operations and Account Management to respond to threats.

Conhecimentos

Analytical thinking

SQL proficiency

Python or R

Client-facing experience

English proficiency

Ferramentas

SQL

Python

R

Descrição da oferta de emprego

Riskified is hiring a Data Analyst to join the Fraud Intelligence team in Lisbon. You will research fraud methods, analyze large datasets, and help build detection tools that power our fraud-prevention engine.

You will collaborate with Data Science, Product, and Engineering to translate insights into actionable improvements. The role requires 2–3+ years of analytics with SQL and experience in R or Python, plus strong communication skills in English.