Structure, organize, integrate and maintain analytical databases from multiple internal and external sources, ensuring consistency, integrity and reliability of the information.
Perform data cleaning, validation and standardization, applying statistical techniques to ensure data quality and analytical accuracy.
Develop and maintain analytical and statistical models, including regressions, time series, multivariate analyses, segmentations and clustering.
Work on data modeling for demand studies, market potential, customer behavior, churn, performance and risk analysis.
Work with georeferenced databases (geomarketing), integrating territorial, demographic and socioeconomic data for spatial analyses and market expansion planning.
Create dashboards, executive reports and analytical datasets that translate large volumes of data into strategic insights with a solid quantitative foundation.
Support Marketing and Commercial teams with data-driven analyses, ensuring methodological alignment and statistical reliability.
Monitor indicators, metrics and KPIs, proposing continuous improvements to the analytical framework and information processes.
Contribute to the advancement of data governance, including best practices for documentation, versioning and standardization of analytical datasets.
Identify opportunities to improve efficiency, competitiveness and analytical accuracy through the structured and intelligent use of data.

Bachelor’s degree in Statistics, Mathematics, Data Science, Engineering, Economics, Information Systems or related fields.
Solid experience in data analysis and modeling.
Proficiency in statistical and analytical techniques (regression, time series, multivariate analyses, clustering).
Experience working with and processing large datasets.
Knowledge of visualization and BI tools (e.g., Power BI, Tableau or similar).
Proficiency in SQL and strong data modeling skills.
Analytical, critical and results-oriented profile, with good communication skills to translate data into business insights.
Differentials / Preferred qualifications:
Previous experience in Marketing, Commercial or Growth teams.
Knowledge of geomarketing and spatial analysis.
Experience with demographic, socioeconomic and territorial data.
Experience with programming languages such as Python or R applied to data analysis.
Experience with cloud data environments.

Data Analyst, Mid-level

Key skills