Data Scientist - Berrini/São Paulo

Develop and enhance predictive models, risk analysis, and data-driven strategies. The professional will be responsible for exploring large volumes of data, building statistical and machine learning models, and generating insights that optimize decision-making in the credit approval process.

Responsibilities:

• Develop, test, and deploy credit risk models, including credit scoring, default propensity, and credit recovery.

• Explore and clean large volumes of data to identify patterns and trends that impact credit risk.

• Create and optimize machine learning models to improve the accuracy of credit decisions.

• Work with data engineering teams to ensure the availability and quality of data used.

• Implement and monitor credit models in production, ensuring performance and compliance with current regulations.

• Develop dashboards and reports to track credit metrics and portfolio behavior.

• Apply Explainable AI (XAI) techniques to ensure transparency in decisions based on predictive models.

• Collaborate with business, risk, and financial product teams to align data-driven strategies.

Requirements:

• Degree in Statistics, Engineering, Computer Science, Mathematics, Economics, or related fields.

• Solid experience with statistical modeling and machine learning, especially in credit-related problems.

• Advanced knowledge of Python, R, or SQL for data analysis and modeling.

• Experience with machine learning libraries and frameworks such as Scikit-learn, XGBoost, TensorFlow, or PyTorch.

• Familiarity with relational and non-relational databases (SQL, NoSQL).

• Experience with handling and cleaning large volumes of data.

• Strong communication and data visualization skills, using Power BI, Tableau, or Matplotlib/Seaborn.

• Knowledge of credit regulations such as Basel, LGPD, and SCR is a plus.

• Experience in deploying models in production environments (MLOps) is a plus.

Differentials:

• Experience in credit modeling at banks, fintechs, or credit bureaus.

• Knowledge in advanced machine learning techniques, such as generative models and deep learning applied to credit.

• Experience with Big Data and cloud computing (AWS, Azure, GCP).

• Experience with pricing models and credit portfolio optimization.

Benefits:

• Competitive salary aligned with the market.

• Hybrid work model.

• Opportunity for professional growth and development.

If you are passionate about data and want to help build innovative solutions for credit, come join our team!

Apply now!