I am the Data Engineer at Launchpad Recruits, where as part of the Data Team I take care of very large datasets including video, candidate review data, platform events, etc. applying multiple big-data and machine learning techniques to help talent and hiring managers make faster, more consistent and fairer hiring decisions.
At Launchpad, and previously at Intern Avenue, I worked in multiple Data Science projects, involving image processing and computer vision techniques, NLP, statistical analysis, sentiment and personality insights and data visualisation amongst others.
Specifically related to data engineering I work setting up scalable data stacks and pipelines requiring knowledge in infrastructure (Linux, containers and VMs), databases (from classic relational to distributed databases), distributed processing engines (Apache Spark) and dashboard/notebook tools (Jupyter, Apache Zeppelin), mainly using Python at the algorithm and application level, but adapting to the platform demands.
Previous to my Data Science/Engineer roles I obtained my PhD from Imperial College London, where I worked within the BICV group in computer vision, image and signal processing, machine learning and pattern recognition.
My PhD thesis focused on the design and development of appearance-based algorithms for extracting distinctive information for two main computer vision applications: object recognition and visual localisation. My main contribution to the field is a biologically-inspired visual localisation algorithm that uses appearance-based methods to model place cell behaviour and artificial neural networks to estimate locations.
Previously, I graduated from Imperial College London (MSc Biomedical Engineering), and from the University of Seville (MEng Electrical and Electronic Engineering) with 1st class honours.