High - impact Data Scientist driving complex data projects leveraging AI tools at dLocal, influencing strategic decisions in payments sector.
About the role
- Data Scientist helping Qliro develop payment solutions through machine-learning in credit and fraud domains. Collaborating in a modern data platform environment to enhance decision-making capabilities.
Responsibilities
- Research, develop, and analyze machine-learning models within the credit domain
- Work with real-time models for credit decisioning and fraud detection
- Develop and improve portfolio-level scoring models
- Monitor model performance, generate insights, and continuously improve existing models
- Brainstorm and engineer new features that drive predictive power and business value
- Contribute to projects that improve our model development processes, tooling, and infrastructure
- Collaborate closely with data science, analytics, engineering, and business stakeholders
- Together with your team, you’ll be a key contributor to improving Qliro’s credit decisions, enabling more of our merchants’ customers to pay seamlessly through smart, data-driven fraud prevention.
Requirements
- Have a strong passion for data and understanding how it connects to real business problems
- Curiosity in how to use software engineering skills to deploy code
- Hold a background in a quantitative field such as engineering, physics, mathematics, statistics, or similar
- Have experience building and deploying models using Python
- Have experience with SQL and are comfortable working with data at scale
- If you have worked with boosted decision trees and neural networks, this is beneficial.
- Are familiar with Git and modern development workflows
- Experience with technologies such as dbt or Airflow is a strong plus — as is experience leading projects across multiple teams or departments.
Benefits
- You’ll join a skilled and ambitious data team working with a modern data platform at the core of Qliro’s decision-making.
- Your work will directly impact how the business operates, scales, and creates value — and you’ll have plenty of room to grow, learn, and shape our data journey going forward.
Job title
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Not specified
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