Fraud Prevention Analyst II

Dlocal; São Paulo; Presencial; BRL 120 000 - 180 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Flexible schedules

Fintech industry environment

Referral bonus program

Social budget for team

dLocal Houses

Resumo da oferta

dLocal is seeking a Fraud Prevention Analyst II in São Paulo to shape fraud strategy across industries. You will decide approvals, design rules, and collaborate with Data Science to refine features and thresholds.

You will own KPIs for key clients, run experiments, and build dashboards to reduce chargebacks while protecting revenue and trust. Join a global fintech team focused on impact, flexibility, and automation.

Qualificações

• Bachelor’s degree in Economics, Engineering, Statistics, or related field.
• 3+ years in fraud prevention or a closely related risk domain.
• Strong SQL and experience working with large datasets.
• Proven experience with AI/ML in fraud or risk scoring (features, thresholds, model-informed rules).
• Advanced English (mandatory).

Responsabilidades

• Continuously analyze transactional data to identify emerging fraud patterns and attack vectors.
• Design, test, and iterate rules that minimize fraud while safeguarding conversion and UX.
• Collaborate with Data Science to enhance features, refine model rules, and set optimal scoring thresholds.
• Evaluate and integrate new datasets to improve data quality, coverage, and signal relevance.
• Own KPIs for key clients and industries; meet with their fraud teams to align on goals and solutions.
• Run experiments (A/B, backtesting) to quantify rule/model impact and guide decisions.
• Build clear monitoring (dashboards/alerts) to track performance, drift, and false positives.
• Identify and drive automation opportunities that reduce manual reviews and errors (e.g., auto-tuning thresholds, rule deployment pipelines).
• Partner with Engineering/Data to implement tooling, integrations, and reporting that accelerate decisioning and incident response.

Conhecimentos

SQL

Fraud prevention

Data analysis

English proficiency

Formação académica

Bachelor's degree in Economics, Engineering, Statistics, or related field

Ferramentas

AWS SageMaker

Athena

QuickSight

Descrição da oferta de emprego

Why should you join dLocal?

dLocal enables the biggest companies in the world to collect payments in 40 countries in emerging markets. Global brands rely on us to increase conversion rates and simplify payment expansion effortlessly. As both a payments processor and a merchant of record where we operate, we make it possible for our merchants to make inroads into the world’s fastest-growing, emerging markets.

By joining us you will be a part of an amazing global team that makes it all happen. Being a part of dLocal means working with 1000+ teammates from 30+ different nationalities and developing an international career that impacts millions of people’s daily lives. We are builders, we never run from a challenge, we are customer-centric, and if this sounds like you, we know you will thrive in our team.

What’s the opportunity?

As our Fraud Prevention Analyst II, you will help us shape fraud strategy across industries, balancing loss reduction with conversion and top-tier user experience. You’ll decide when to approve or reject payments, using data, experimentation, and close collaboration with Data Science to improve model features and thresholds. You’ll own KPIs for key clients and verticals, translating their needs into effective controls. A core part of your impact will be streamlining workflows and reducing manual review through smarter rules and tooling. Your work will directly lower chargebacks/claims while protecting revenue and customer trust.

What will I be doing?

• Continuously analyze transactional data to identify emerging fraud patterns and attack vectors.
• Design, test, and iterate rules that minimize fraud while safeguarding conversion and UX.
• Collaborate with Data Science to enhance features, refine model rules, and set optimal scoring thresholds.
• Evaluate and integrate new datasets to improve data quality, coverage, and signal relevance.
• Own KPIs for key clients and industries; meet with their fraud teams to align on goals and solutions.
• Run experiments (A/B, backtesting) to quantify rule/model impact and guide decisions.
• Build clear monitoring (dashboards/alerts) to track performance, drift, and false positives.
• Identify and drive automation opportunities that reduce manual reviews and errors (e.g., auto-tuning thresholds, rule deployment pipelines).
• Partner with Engineering/Data to implement tooling, integrations, and reporting that accelerate decisioning and incident response.

What skills do I need?

• Bachelor’s degree in Economics, Engineering, Statistics, or related field.
• 3+ years in fraud prevention or a closely related risk domain.
• Strong SQL and experience working with large datasets.
• Proven experience with AI/ML in fraud or risk scoring (features, thresholds, model-informed rules).
• Strong analytical, presentation, and communication skills; able to translate insights into action.
• Automation mindset: comfortable with tools and workflows; familiarity with AWS SageMaker, Athena, or QuickSight is a plus.
• Advanced English (mandatory).

What do we offer?

Besides the tailored benefits we have for each country, dLocal will help you thrive and go that extra mile by offering you:

• Flexibility: we have flexible schedules and we are driven by performance.
• Fintech industry: work in a dynamic and ever-evolving environment, with plenty to build and boost your creativity.
• Referral bonus program: our internal talents are the best recruiters - refer someone ideal for a role and get rewarded.
• Social budget: you\'ll get a monthly budget to chill out with your team (in person or remotely) and deepen your connections!
• dLocal Houses: want to rent a house to spend one week anywhere in the world coworking with your team? We’ve got your back!

Flexibility in how you work

We focus on impact and productivity over fixed hours. This means our teams have flexible schedules and, depending on your role and location, you will combine self‑managed focus time with moments of in‑person connection in our collaboration hubs.