Marketing solutions for US Clients. Conversions forecasting with machine learning algorithms (using spend in campaigns, impressions, clicks, and several google analytics information), elasticity calculus of Conversions to Call to Actions in web pages. Spend recommendation given econometric model results and based on point of diminishing returns for Cost per Acquisition metric. Incrementality testing on iROAs using A/B testing and TBR/GBR techniques (Time Based Regression and Geox Based Regression). Full programmed in python, interconnecting with SQL MS Management Studio Database. Also pulling data from google ads and google analytics. Client reporting in Tableau and PBI.

Development of prediction and elasticity models in python. Master data management with SQL. Development of fraud models and detection of anomalies in logistics (neural networks). KPIs generation and presentation on interactive dashboards.

Validation of banking credit risk models with exhaustive econometric analysis in R and Python. Benchmark models development and implementation of machine learning algorithms for defaults prediction. Typical models: PD, LGD, EAD , Stress Testing. Implementation of Random Forest, Boosting Machines and Neural Networks with time series.

Data cleaning and analysis under Unix environment. Exploration of relational databases in SQL. Marketing campaigns modeling and analysis of its impact over incremental volume of sales for big Companies from USA. Econometric models programming and forecasts execution in SAS and R.

Tax Analysis at Financial Services Office for mutual funds. K1-s preparation with the corresponding tax allocation to partners from Hedgefunds. Returns preparation to report the IRS , and large databases exploration with SQL.

Department of Science and Technology. Topic: “The school dropout on distance education”. Structural Equations Model (SEM) programmed in R and Stata. Exhaustive econometric and statistical analyses over several hypothesis testing.