Leonardo Arbelaez

-Work with large data sets from different source systems, transforming and cleaning online and offline data to discover actionable insights -Develop easy to understand visualizations to convey insights to dealers and present clear calls to action -Extract, clean and transform customer and consumer data from across Government agencies for the purposes of analysis, modeling, and prediction -Predictive Model Development and Data Mining -Use predictive modeling to increase and optimize customer experiences

* Data Cleaning / pre-processing (of both traditional and alternative data) * Developing / Implementing models with various machine learning strategies, in an attempt to find repeating, predictable patterns in how market activity responds to data patterns * Using quantitative techniques (from descriptive statistics, predictive modeling & forecasting, to prescriptive analytics including decision analysis, math programming, simulation, machine learning) to resolve business problems (using Python)

Modernization of legacy systems, Data migration, ETL, Data Warehouse, MS Power BI

Modernization of legacy systems, Data migration, ETL, Data Warehouse, Business Intelligence

POS, ERP, Salesforce, MDM, ETL, Data Warehouse, Data Architecture, Information Security

- ERP, SOX, Compliance, DRP, MDM, salesforce

ETL, CRM, ERP, ODS, Informatica, Siebel,

- ERP, SOX, Compliance, DRP

DS102X: Machine Learning for Data Science and Analytics Credential ID: b457b92d29ca43e5b9f4838408a78cc4

R Programming, Exploratory Analysis, Statistical inference, Regression Models, practical machine learning algorithms

Business Analysis

Information Systems, International business