Job Description
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 part of the Fraud Prevention team, you will work on deciding the fraud prevention strategy for each industry. The objective will be to optimize the decision of which payments we have to reject and make decisions that continue to improve the user experience, keeping in mind the chargeback/Claims and conversion rate targets.
What will I be doing?
- Identifying fraud patterns through continuous data analysis & review of previous fraud incidents.
- Developing efficient rules that balance reducing fraud and maintaining the conversion rate.
- Collaborating with the data science team to improve and create new features and machine learning model rules while setting the appropriate thresholds for transactional scoring systems.
- Analyzing new databases to enhance the quality and relevance of available data.
- Being responsible for the KPIs of key clients and major industries, considering their unique needs and requests. You’ll also meet with their fraud teams to deliver the best solutions.
- Lead and participate in cross-team projects to improve scalability, develop automations, and enhance AI capabilities in the fraud industry.
What skills do I need?
- Bachelor’s degree in Economics, Engineering, Statistics, or related field.
- 1-3 years of experience in fraud prevention or a similar industry.
- Proficiency in handling large databases; SQL is a must.
- Knowledge of Python or a similar data-oriented language, such as R, is a plus.
- Experience with data management tools such as AWS Sagemaker, Athena, or Quicksight is a bonus.
- Strong analytical skills and compassion for discovering new patterns and making data-driven decisions.
- Attention to detail without losing sight of the big picture.
- Enthusiastic, proactive, team player, and problem-solver.
- Fluent in written and spoken English.
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.
- Learning & development: get access to a Premium Coursera subscription.
- Language classes: we provide free English, Spanish, or Portuguese classes.
- 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!
What happens after you apply?
Our Talent Acquisition team is invested in creating the best candidate experience possible, so don’t worry, you will definitely hear from us. We will review your CV and keep you posted by email at every step of the process!
Also, you can check out our webpage, Linkedin and Youtube for more about dLocal!
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
