Fully dedicated to the sales forecasting project of several LATAM countries

Full-time dedicated to the Pinterest Ads Intelligence team.Main project: https://medium.com/pinterest-engineering/campaign-budgets-at-pinterest-be94f15a4527

Plan and execute data analysis/model development for the internal client:- Customer sentiment analysis;- Time series modeling;- Hypothesis testing to optimize campaigns and product offer;- Cluster analysis and customer segmentation

Furnish campaign managers with insights, analytical reports and recommendations enabling effective strategic planning. Main activities include:- Design controlled experiments to drive statistical significant campaign results and conduct hypothesis tests.- Analyze campaign results using ANOVA, Cluster analysis and Regression models aiming to optimize ROI and customer acquisition.- Report Direct Mail and Online Campaign results to high level business managers.- SAS/SQL/Python… Show more Furnish campaign managers with insights, analytical reports and recommendations enabling effective strategic planning. Main activities include:- Design controlled experiments to drive statistical significant campaign results and conduct hypothesis tests.- Analyze campaign results using ANOVA, Cluster analysis and Regression models aiming to optimize ROI and customer acquisition.- Report Direct Mail and Online Campaign results to high level business managers.- SAS/SQL/Python instructor in the company’s Data Science Program.- Reporting Manager of some co-workers. Show less

- Design controlled experiments to drive statistical significant campaign results and conduct hypothesis tests. - Analyze campaign results using ANOVA, Cluster analysis and Regression models aiming to optimize ROI and customer acquisition. - Report Direct Mail and Online Campaign results to high level business managers. - SAS/SQL/Python instructor in the company’s Data Science Program.

Developed data science algorithms and processes that provided predictions and insights on customer experience- Development of predictive models to report KPIs related to quality in customer service.- Measure quality of customer service analyzing equipment log data and call center data.- Collect, clean and prepare data for any type of ad hoc analysis and reports.

- Application of PDs and LGDs for IFRS and Capital Requirements on customer data. - Development of a process in SAS for Monitoring customers with great propensity to risk.- Ad hoc data analysis to find patterns among the types of credits with higher risk.