In this role, you will lead the development of data science solutions applied to credit products, ensuring robust, scalable, and production-ready machine learning systems.

• Lead end-to-end data science projects, from problem definition with product and operations teams to model deployment in production environments
• Develop and maintain machine learning models for credit applications, behavioral analysis, and collections strategies
• Monitor model performance and data quality, including drift detection (data drift and concept drift) using modern frameworks
• Build and maintain KPIs, dashboards, and analytical reports to support credit strategy and operational decision-making
• Conduct exploratory analysis to identify patterns, risks, and opportunities that improve credit efficiency and portfolio performance
• Collaborate closely with credit, risk, and operations teams to ensure alignment between models and business needs
• Stay up to date with data science best practices and AI-assisted development tools, driving continuous improvement in delivery quality

Requirements

The ideal profile combines strong technical expertise in machine learning with solid statistical knowledge and hands-on experience in credit-related data products.

• Strong experience with machine learning models applied to business problems such as classification, regression, and time series forecasting
• Proven experience with credit models (application, behavior, or collections), especially in B2B or postpaid credit environments
• Advanced proficiency in Python, SQL, and Spark for large-scale data processing and analysis
• Solid understanding of statistics, hypothesis testing, and statistical inference
• Experience working with version control tools such as Git
• Ability to translate complex technical findings into clear business insights
• Degree in Computer Science, Engineering, Statistics, Mathematics, Physics, or related fields (or equivalent practical experience)

Differentials:

• Experience with Databricks ecosystem (Model Serving, Unity Catalog, automation bundles)
• Exposure to AWS cloud environments
• Knowledge of MLOps frameworks such as MLflow
• Experience with causal inference techniques (e.g., A/B testing, instrumental variables, Bayesian methods)
• Familiarity with AI agents and LLM-based automation systems
• Experience with receivables anticipation products or fintech credit solutions

Benefits

• CLT contract with full-time work schedule (8 hours/day, Monday to Friday)
• Comprehensive health and dental insurance with no co-participation
• Life insurance coverage and wellness support programs
• Flexible food allowance via card system
• Home office support, including equipment and mobility assistance
• Remote-first structure with access to coworking spaces nationwide
• Education support, including subsidized courses, degrees, and language learning
• Mental health and nutrition support via specialized platforms
• Parental support benefits, including extended maternity/paternity leave and childcare assistance
• Performance bonuses, stock options, and career growth opportunities
• Collaborative and innovation-driven fintech environment.

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

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