Tech Lead on Data Projects

The objective was to propose quantities to be produced per product to minimize losses due to stock breakage or expiration. We develop a demand forecasting model, a stock evolution simulator and a web panel to view and download the results.
Main technologies: R, Shiny.
Modeling techniques: simulation and optimization techniques.

Development of a management application for large IoT systems in buildings to measure supplies use, temperature, air quality and others. Integrated in Metasys, a world’s leading building automation system.

Main technologies: Python, Flask, React.js, PostgreSQL.

Automation of the process of mortality data ingestion from civil registries, processing, modeling and generating reports and alerts from MOMO. The objectives were to alert and measure excesses and attribute mortality to events such as heat waves or flu.
MOMO received a lot of attention during the Coronavirus health crisis and it was a key project to estimate the real impact of the epidemic on Spanish mortality.

During the health crisis, I also developed the ISCIII data publication and monitoring panel, and the calculation of the reproducibility index by region, which was reported to other organizations.

Main technologies: R, Python, Docker, Flask, Flexdashboard.
Modeling techniques: GAM, mixed-effects models, survival analysis.

Design, develop and deploy the Data Warehouse to analyze the e-scooter sharing quality service, follow the vehicles incidences, the customers behavior and take strategic decisions. I led the tech team.
The goals we achieved:

• Connect different data sources, such as the application backend and the bike log system in BigQuery, apply the business logic and register all the main KPIs in the DWH.
• Automatize all the ingestion processes involved in a robust pipeline in Google Cloud Platform.
• Design and develop an interactive dashboard for different kind of users (Quality, Business and Marketing teams), including data restriction access depending on the role.
• Mentor and train the client’s internal team to maintain and evolve the system.

Main technologies: Python, Flask, Dash, PostgreSQL, GCP.

Development of a system to analyze people transit in physical spaces through cameras. My main objectives were:

• Set up the infrastructure, the store management websites and the cameras and the transit analysis dashboard.
• Create the heatmaps on the store plans based on the information received from the cameras.
• Design and develop a dashboard to analyze the hot and cold areas, the user behavior and the main KPIs across the stores.

Main technologies: R Shiny, Python Flask, Bootstrap, Google Cloud (Compute Engine, Cloud Functions and BigQuery).
Modeling techniques: trigonometry, minimization of error functions.

Development of a prediction system for openings and clicks in an email marketing system.
The objectives:

• Avoid sending to users with almost zero probabilities of clicks and opens
• Increase the reputation of the system with the email provider
• Optimize the income of the daily schedule automatically assigning emails to users

Main technologies: Python, Docker, AWS, MySQL
Modeling techniques: random forests, linear optimization.

Creation of machine learning processes to increase the performance of Google Ads campaigns. Specialization in:

• Natural language processing techniques
• Data processing and modeling
• Cloud architecture

Main technologies: Python, Docker, Google Cloud (Compute Engine, Cloud Build, BigQuery, GKE, datastore).
Modeling techniques: TFIDF, cosine distance and other NLP and other common techniques in NLP.

Modeling of production in wind and solar generators based on sensor readings to detect machine failures. Integration with the customer IoT system and report automation. Development of an API to order actions and view system results.
Main technologies: ElasticSearch, Python, AWS, MySQL.
Modeling techniques: random forests.