Why you should 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, in a flexible, remote-first dynamic culture with travel, health, and learning benefits, among others. Being a part of dLocal means working with 900+ teammates from 25+ 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.
As part of the Fraud Prevention Tactics 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 and conversion rate targets.
What will I be doing?
- Identifying fraud patterns by continuous data analysis & review of previous fraud.
- Developing efficient rules that strike a balance between reducing fraud and maintaining the conversion rate.
- Collaborating with the data science team to improve and create new features a 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.
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 similar data-oriented languages like R is a plus.
- Experience with data management tools such as AWS Sagemaker, Athena, or Quicksigh it's 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 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!
