Commercial Data Analyst II

Role Overview

• Develop and apply analytical, statistical and predictive models focused on the commercial business, using data science techniques to generate insights, forecasts and recommendations that support strategic decisions and improve the performance of the sales area.
• Collect, integrate and prepare large volumes of commercial data from multiple sources (ERP, CRM, internal systems and external databases), using Python, SQL and Power Query, ensuring data quality, consistency and governance.
• Perform exploratory data analysis (EDA) to identify patterns, trends, customer behaviors, opportunities and risks in commercial performance.
• Develop, train, evaluate and maintain statistical and machine learning models applied to the commercial context, such as sales forecasting, demand analysis, customer/product segmentation and clustering, churn models, profitability and purchase behavior.
• Apply time series, regression, classification and clustering techniques using libraries such as pandas, numpy, scikit-learn and statsmodels.
• Create and validate performance metrics and analytical indicators, ensuring alignment with business rules and strategic objectives.
• Develop simulations and scenarios to support budgeting decisions, commercial targets, market analysis and sales planning.
• Automate analytical pipelines and modeling routines, from data ingestion to generation of analytical outputs.
• Support communication of results through analytical visualizations and Power BI dashboards, focusing on model validation and interpretation (not just reporting).
• Translate technical results and complex models into clear, actionable, business-oriented insights to support managers and commercial teams.
• Work closely with business, technology and BI teams to advance the analytical maturity of the commercial area.
• Drive continuous improvement of analytical processes by adopting best practices in version control, documentation, reproducibility and model monitoring.

Requirements

• Bachelor's degree in Data Science, Statistics, Mathematics, Economics, Engineering, Computer Science or related fields.
• Intermediate/advanced Python for data analysis and modeling (pandas, numpy, scikit-learn, statsmodels, matplotlib/seaborn).
• Intermediate/advanced SQL for data extraction, manipulation and analysis.
• Knowledge of descriptive and inferential statistics, regression and time series analysis.
• Experience with data preparation, feature engineering and model validation.
• Knowledge of Power BI for visualization and validation of analytical results.
• Minimum of 6 months of experience in the area or related fields.
• Experience with predictive models applied to sales is a plus.
• Experience with sales forecasting and demand analysis.
• Knowledge of supervised and unsupervised machine learning.
• Experience with automation of analytical pipelines will be considered a plus.
• Experience working in data-driven environments and making decisions based on models.

Tech Stack

• ERP
• Numpy
• Pandas
• Python
• Scikit-Learn
• SQL

Benefits

• Health plan with the possibility to include dependents under specific conditions.
• Accessible dental plan with the possibility to include dependents under specific conditions.
• Wellhub (formerly Gympass) for access to gyms, personal trainers and health apps.
• Chronic disease support program.
• Psychological counseling.
• Birthday Day Off: Celebrate your day in style!
• Hybrid Work*: Remote work up to two days per week.
• Flexible Hours*: Start time between 7:00 and 9:00.
• Extended Paternity Leave: 20 days to support the arrival of a new family member.
• Hybrid model after maternity leave*: Initiative to facilitate the transition back to work for employees returning from maternity leave.
• Support program for pregnant employees and for the baby's first year of life.
• Life Insurance: Protection for you and your dependents.
• Corporate University with continuous training programs aligned with leading learning methodologies.
• Unpaid leave of up to 12 months — a pause to focus on learning and development in your area of expertise.
• Profit Sharing (PLR): Recognition for achieving established goals.
• Private Pension Plan: Opportunity for financial reserve with company contribution, tax incentives and options for withdrawal or future income.
• Grocery allowance: Provided on an electronic card.
• Meals: On-site cafeteria or meal voucher (depending on location and role).
• Transportation: Commuter benefits or company shuttle (depending on location and role).
• Exclusive Discounts for you and your family: Take advantage of benefits on partner products and services, including universities, language courses, multi-brand stores, pharmacies, pet plans, eyewear and much more!