Javier Sáez Gallego

Contributed to defining and developing key-company products with a data centric perspective, ranging from deploying machine learning models, implementing geospatial algorithms, and building APIs and data ingestion pipelines. More details are below:

- Co-define a forest monitoring product that leverages near-real-time satellite images to enhance the transparency of the carbon credits. Develop and deploy machine learning models in production in a Kubernetes cluster.

- Develop a geospatial splitting service to support the company's core product of collaborative reforestation.

- Implement several data ingestion pipelines to process voluntary carbon market data.

- Support various web app developments and company tasks by deploying APIs, managing databases, and creating dashboards.

As a consultant, I contributed to identifying potential business cases where machine learning models could bring value to the clients. On a practical level, I participated in the research, development, and implementation of predictive maintenance models of ATMs for one of the biggest banks in Europe. Developed dashboards and interactive graphs.

I was responsible for creating business value with available data from existing clients, focusing on data-driven actions. I worked on two projects: predictive maintenance of factory areas and optimal scheduling of hydroelectrical power plants. As the first data scientist in the company, I was also responsible for teaching my colleagues the principles of data science and machine learning.