Fraud Prevention Analyst II

dLocal; Buenos Aires; Presencial; ARS 1.800.000 - 2.800.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Flexible schedules

Referral bonus program

Social budget

dLocal Houses

Descripción de la vacante

dLocal is seeking a Fraud Prevention Analyst II in Buenos Aires to shape fraud strategy across industries, balancing loss reduction with conversion and user experience. You will design rules, work with Data Science, own KPIs for key clients, run experiments, and build monitoring dashboards to reduce fraud while protecting revenue and trust.

This role sits in a dynamic fintech environment, offering cross-functional collaboration, automation opportunities, and a chance to advance fraud analytics

Formación

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

Responsabilidades

• Continuously analyze transactional data to identify emerging fraud patterns and attack vectors.
• Design, test, and iterate rules to minimize fraud while safeguarding conversion and UX.
• Collaborate with Data Science to enhance features, refine model rules, and set scoring thresholds.
• Evaluate and integrate new datasets to improve data quality and signal relevance.
• Own KPIs for key clients and industries; align with their fraud teams.
• Run experiments (A/B, backtesting) to quantify rule/model impact.
• Build dashboards and alerts to monitor performance, drift, and false positives.
• Identify automation opportunities to reduce manual reviews and errors.
• Partner with Engineering/Data to implement tooling, integrations, and reporting.

Conocimientos

SQL

Data analysis

Fraud detection

AI/ML fraud

English (Advanced)

Educación

Economics/Engineering/Statistics degree

Herramientas

AWS SageMaker

AWS Athena

AWS QuickSight

Descripción del empleo

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.