Priscila Hohberg

Analysing customer how customers navigate our products. Developing analysis and building data products and recommendations to help Product Managers making decisions based on data. Currently supporting Activations US, Reactivations INTL and Re-engagement US squads. Tools: Python, SQL, A/B testing, GA tracking, Tableau

Understanding the customer's behavior using data analysis. Building visualizations to facilitate access to key CRM information. Tools: R, RStudio, SQL, Looker, Git, Snowflake

Statistical modeling of propensity to buy and consume financial products such as personal loans. Automatic and standardized performance reports and current model analysis. Customer segmentation, profile analysis, lifetime as customer, purchase recency. Strategic structuring of communication rules for different customer profiles, aiming to maintain the business relationship and increase their spending. Presentation of analysis and results for other areas of the company.

Sending SMS actions for product offerings and all previous processing: profile selection, manipulation and understanding of large databases. Calculating the return of these actions with calculation of ROI and other indicators. Stock return reports. Estimation and monitoring of propensity models for personal loan product.

Statistical modeling for fuel demand forecasting using time series methods. Update of management reports with strategic indicators for the company. Follow-up of the Federal Official Gazette to collect strategic information.

Meetings and understanding, with article reading of classification techniques, such as the CLARA and PAM algorithms.

Understanding and calculating the percentage of molecules created from another, larger, subjected to high energy electrons. Reading articles to verify which prebiotic molecules were found in regions of the Interstellar Medium with energy level similar to those simulated in the laboratory (LNLS - Synchrotron Light Laboratory). Visit LNLS to follow and understand how the experiments are done.

Time series forecast: final project was to predict the legal amout of biofuel's cars for the next year.