Summary
David Mattos is a Data Scientist with a Ph.D. in Software Engineering and 10 years of experience applying causal inference and experimentation to complex, real-world systems. At Volvo Cars he is the main data scientist for Vehicle Engineering, building over 80 data pipelines, 50+ live reports and 10 custom web apps that support more than 1,000 engineers across chassis, climate, interior and manufacturing domains. He specializes in designing scalable data architectures, large-dataset database migrations, vehicle time-series analysis tools (Python/Spark/SQL) and integrating heterogeneous sources like vehicle telematics, weather and warranty to drive quality and cost-reduction decisions. David combines applied AI/ML and rigorous statistical methods—especially structural causal models and Bayesian analysis—to enable A/B testing in embedded systems and to draw causal conclusions from observational data. He has both academic depth from WASP research on automating field experiments and hands-on product impact, with his tools used daily by over 200 colleagues. A less obvious strength is his ability to translate experimental design into production-ready analytics that bridge research, engineering and decision-making.
10 years of coding experience
1 year of employment as a software developer
Master’s Degree, Electrical and Electronics Engineering, Master’s Degree, Electrical and Electronics Engineering at Instituto Tecnológico de Aeronáutica - ITA
Doctor of Philosophy (Ph.D.), Computer Software Engineering, Doctor of Philosophy (Ph.D.), Computer Software Engineering at Chalmers University of Technology
English, Spanish, Portuguese, Swedish