I am the Data Engineer Lead 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), cloud deployments (CI tools, AWS) 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.