DATA SCIENTIST III - ANALYTCS & MODELING - INTER PAG

About the Role and Mission

We are seeking a Senior Data Scientist - Analytics & Modeling to strengthen our Data & Analytics team. Your mission will be to develop the area's first data science models, transforming data into strategic insights that drive business decisions and acting as a technical reference. You will build bridges between statistical analysis, predictive modeling, and the needs of the PJ, Products, Pricing, and Commercial departments — delivering studies and models that generate real and measurable value for the organization.

This is a strategic role with the challenge of pioneering the construction of the data science area, while ensuring the quality of current analyses. If you are passionate about solving complex problems, have a winning mindset, and relentlessly pursue excellence, your place is here.

Your Day-to-Day Responsibilities

• Develop data science models from scratch (churn, segmentation, propensity, scoring, forecasting).
• Write complex SQL queries to investigate customer base behavior and product performance.
• Conduct financial analyses and studies that support strategic decisions of the management.
• Act as a strategic partner to the commercial planning, commercial, product, and operations areas.
• Translate business problems into analytical solutions and predictive models.
• Present results and recommendations to stakeholders at different levels.
• Implement and manage models in AWS SageMaker.
• Support pricing studies and profitability analyses.

Requirements

Mandatory:

• Education in quantitative fields (Statistics, Mathematics, Economics, Engineering, Computer Science, or related).
• Advanced SQL (complex queries, CTEs, window functions, optimization).
• Python for data science (Pandas, NumPy, Scikit-learn, Statsmodels).
• Advanced Excel for financial analyses and modeling.
• Experience working with multiple stakeholders at different levels.
• Ability to communicate technical results to non-technical audiences.
• Autonomy to act as a data science reference in the area.

Desirable:

• Knowledge of AWS SageMaker.
• Experience with predictive modeling (churn, segmentation, scoring, pricing).
• Experience in acquiring or financial sectors.
• Mastery of financial concepts (P&L, profitability).
• Experience with executive presentations (PowerPoint).