8+ years of experience alternating the work in academia and as freelance consultant and event manager. Fast learner of new computational technologies with a deep love for maps. Profcient in data processing, data modelling, and interactive reports, as well as in scripting languages including Python and R.
I have extensive professional experience working in scientific programming and data science in multiple fields, such as bioinformatics, computational biology, microscopy image analysis, and, more recently, geospatial analysis. I developed these projects through multiple international experiences (Spain, France, Japan, the U.S.A, and Switzerland) in both industry and academia. During these, I was in direct contact with research at different levels, developing and improving the reproducibility of computational analytical pipelines and applying machine learning procedures to solve scientific questions. My main programming languages are Python, R, Bash, and Ruby, and my primary machine-learning framework is PyTorch.
While studying for my Bachelor in Biology at the University of Malaga, I developed a particular interest in computational biology to understand biological systems better. After completing my Bachelor’s, I undertook a University Master in Cognitive Sciences at the University of Malaga, a program that offered an interdisciplinary approach to cognitive neuroscience and provided training in cutting-edge statistical techniques, including machine learning. More recently, I enrolled in the Lemanic Neuroscience Doctoral School (LDNS) at the University of Lausanne where I have worked for the last four years as Ph.D. candidate. In my thesis project, I developed a brand new tool in python able to perform an integrative analysis of multiple data modalities, such as microscopy image analysis, electrophysiology, behavior recordings, and genetic datasets. In parallel, I deployed and maintained the central analysis server for the lab group based in Jupyter Hub and implemented protocols for improving reproducibility and documentation in our research. Furthermore, this experience sat me together with experimentalists and researchers with a low level of analysis expertise, which gave me valuable insights about making tools and interfaces most appealing for this segment of researchers.
In parallel to my research experience, I funded and coordinated “Impaciencia”, an educational project to promote interdisciplinary research among bachelor students. This project involved coordinating a team of 10 people, and required the coordination with 6 universities and 16 companies. This entrepreneurial side of me complements my passion and expertise for science, leading me to develop two start-up attempts: “Scidream” (2015 UMA Spin-off contest), and “Tell Me More” (2020 Innosuisse Bussiness Concept Training Program). Both of them discontinued after business plan evaluation. Finally, currently, I work as a freelance consultant and external data scientist for startups and institutions developing scientific products. Two recent examples are developing a deep learning model for satellite image analysis for Kido Dynamics (ESA-BIC, Switzerland) and consulting sessions to support a pre-initial investment round for Coolx.earth (Demium, Spain).