Ferran Vidal-Codina

Data scientist · AI/ML engineer · MIT PhD

I build production AI, data systems and models for complex, high-stakes domains.

My career spans nine years across research and engineering, including production work for FIFA, Google, the English Premier League, the Golden State Warriors, FC Internazionale, and US Soccer. I turn difficult data and modeling problems into systems people can trust and use.

FVC / 01 Ferran Vidal-Codina

Selected projects

Problem → approach → measurable result

Across the stack

I’m happiest when I can follow a problem end to end: get the data from wherever it lives, validate it and make sure it’s consistent, build the model or workflow, and extract insights and value for the stakeholders who need them. I’ve done the work at every layer of the data value chain, so I know exactly where handoffs tend to break down.

How I work

I start with a thorough understanding of the problem and its requirements, then build small and put the work in front of the people who need it early. From there I stay close to the rough edges: the data that exhibits inconsistencies, the cases a model misses, and the general messiness that accompanies real systems. That is where attention to detail matters most, and where I spend real time translating what the data means for stakeholders who may not be technical.

Recognition

2022

Paper of the Year

International Sports Engineering Association and Springer Sports Engineering, for Automatic event detection in football using tracking data.

2011–2013

La Caixa Foundation Fellowship

$150,000 fellowship supporting graduate study at MIT.

Contact

Based in Hawai‘i and working remotely across US time zones. Reach me at vc.ferran@gmail.com or on LinkedIn. Research record: ORCID.