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).