Design and develop an Anomaly Detection framework based in python to detect outliers in Equity Models and Factor Models datasets. This project included the definition of all steps in the workflow, from data engineering to reporting, including an interface to tune settings and visualize outputs in each stage. Machine learning models were used in an ensemble and different approaches were combined to find the most anomalous observations while reducing the number of false positives.

Developed text classification models for different types of events based in police reports. This project included:- Creating a web interface to manually set labels and extract important information based in event summaries.- Manipulate data to obtain meaningful temporal, spatial and text-based features.- Tune model parameters using cross-validation.Developed a prototype of an application to monitor security topics in México based on tweets and news articles.

- Developed a prototype to automate narrative generation for monthly reports with Python and Yseop. Features were extracted from model data and used to construct sentences that described changes in global economic conditions. - Enhanced and implemented quality assurance functions that detect issues in input data as well as abnormal behavior while calculating model outputs.- Followed the software development life cycle to develop, test, and introduce changes to the code base.

Design and implementation of an analytic development framework in R and Python, which included functionality for:- Consuming data from a centralized database using query templates.- Data cleansing, outlier removal, imputing missing values, and normalization, and data visualization.- Feature extraction on time-series.- Feature selection using statistical tests and machine learning methods, such as ANOVA, Kolmogorov-Smirnov, Linear, Logistic Regression and Linear Support Vector Classifier (LSVC) with regularization, Random Forests, and others.- Model tuning and verification using cross-validation.Other activities included:- Optimization of model parameters using numerical and search methods.- Anomaly detection of parameter co-variances using mixture models.- Setup of a Hadoop cluster, implementation of map-reduce jobs, and loading and processing data on Hive and Cassandra databases.

- Developing front-end and back-end for applications in Microsoft.- Database administration, migration, and backup.- Design of queries and stored procedures to generate reports in MS SQL Server.Major customers were international companies such as CEMEX and PEPSICO.

Developing web pages using Drupal framework:- Online stores- Catalogs- Theme customization using CSS- Photo and video galleries- Google analytics campaigns

- SCADA system administration. - Process simulation on PLC. - Database administration, backup, and analysis.- Modification of PLC ladder diagrams and technical support. - Design and modification of graphical user interface for plant operators. - Remote support for plants.- On-site technical support on plant maintenance operations.