Summary
Josep Arús-pous is an associate director of data science and machine learning with 11 years of experience building and operationalizing deep learning systems, primarily in healthtech and drug discovery. He holds a PhD in cheminformatics and has designed generative models and large-scale data pipelines to explore billion-molecule databases, bridging research-grade innovation with production engineering. At Evinova and previously at AstraZeneca and Roche he leads cross-functional teams to deliver AI-driven clinical trial and therapeutic solutions, spanning model development, data engineering, mobile apps for patient monitoring, and cloud deployment. He combines strong systems and UNIX administration roots with modern ML tooling (PyTorch, Spark, DevOps), enabling end-to-end ownership from data ingestion to scalable inference. Outside work he’s a self-described science-and-music nerd, reflecting a curiosity that drove him to build computing clusters and production platforms during his PhD. Practical, research-savvy, and product-focused, he excels at rethinking ML systems from first principles and shipping them into real-world healthcare contexts.
11 years of coding experience
13 years of employment as a software developer
PhD in Chemistry and Molecular Sciences Computer-assisted drug discovery (Cheminformatics), PhD in Chemistry and Molecular Sciences Computer-assisted drug discovery (Cheminformatics) at University of Bern
Certificate of Proficiency in English (CPE) English, Certificate of Proficiency in English (CPE) English at British Council
Master’s Degree Bioinformatics, Master’s Degree Bioinformatics at Universitat Pompeu Fabra
UPC Universitat Politècnica de Catalunya
English, Spanish, Catalan, German