Summary
Sarah Jarvis is a Technical Product Manager and former leader of applied machine learning with 10 years’ experience turning research-grade AI into production-ready products across healthcare, logistics and automotive. Based in Cambridge, she blends deep technical roots—PhD-level computational neuroscience and hands-on Python tooling—with strategic product skills to define roadmaps, value cases and innovation pathways that scale. At Solvo.ai she expanded addressable market by 160% and helped triple commercial lead engagement by connecting ML choices to customer data constraints and sales workflows. Previously she led ML teams at Secondmind and Babylon, introducing TRL-style standards, delivery-focused ML strategy and mentorship structures that improved retention and prototyping velocity. Comfortable translating complex science for stakeholders and public audiences, she has a track record of reducing analysis time from days to hours while preserving technical rigor. Unusually, her background in optogenetics and population health modelling informs a practical curiosity for cross-disciplinary, human-centered AI solutions.
10 years of coding experience
6 years of employment as a software developer
Bachelor of Engineering (B.Eng.) / M. Biomed Eng., Computer Engineering, Biomedical Engineering, Bachelor of Engineering (B.Eng.) / M. Biomed Eng., Computer Engineering, Biomedical Engineering at University of New South Wales
Postdoctoral studies, Bioengineering and Biomedical Engineering, Postdoctoral studies, Bioengineering and Biomedical Engineering at Imperial College London
Doctor of Philosophy (PhD), Computational neuroscience, summa cum laude, Doctor of Philosophy (PhD), Computational neuroscience, summa cum laude at Albert-Ludwigs-Universität Freiburg im Breisgau
German, Spanish, English