Fraud Data Analyst - Satispay

Satispay
Barcelona, Spain
14 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience required
7 years minimum
Working hours
Regular working hours
Languages
English

Tech stack

Python (Programming Language) Machine Learning Standard Sql SQL Databases Pyspark Performance Monitor Graphql

Job description

OverviewIn this role you will help secure digital payments by designing real-time defense strategies.You will work closely with Product and Engineering to shape the decisioning stack and translate fraud patterns into high-impact rules.You’ll balance security with a smooth user experience, reducing friction while protecting users.This position offers fast-paced collaboration and the chance to influence risk strategy at scale in a growing fintech platform.Compensaciones / BeneficiosPrivate health insurance for you and your familyStock option planRelocation supportProfessional development programsUnlimited PTOHybrid working policy with flexible hoursResponsabilidadesArchitect real-time decisioning strategies for fast-millisecond decisionsDevelop precise, high-performing fraud rules to balance false positives and fraud lossInvestigate and mitigate emerging payment fraud schemes (e.g., ATO, social engineering)Collaborate with Product and Engineering to define analytical requirements for new features and data signalsOperationalize ML models with heuristic rules in the decisioning stackAssess security measures to minimize unnecessary user friction while maintaining protectionProvide strategic performance reporting to leadership on rule efficacy and risk postureRequisitos principales3-7 years of professional experience in risk, payments, or creditStrong SQL and Python for data analysis and strategy developmentSolid understanding of payment fraud dynamics and real-time decisioning environmentsExcellent English communication skillsNice to Have: Machine Learning, Data Science, PySpark, GraphQLteamworkproblem-solvingcuriositySQLPythonreal-time decisioning

Requirements

Requisitos principales3-7 years of professional experience in risk, payments, or credit Strong SQL and Python for data analysis and strategy development Solid understanding of payment fraud dynamics and real-time decisioning environments Excellent English communication skills Nice to Have: Machine Learning, Data Science, PySpark, GraphQL teamwork problem-solving curiosity SQL Python real-time decisioning

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