Official Story
Friederike started a PhD degree in 2008 in Cognitive Neurosience at the ICN (UCL), with degrees in cognitive science and philosophy, researching free will. Inevitably, she concluded that neuroscience is not well suited to solve philosophical questions. She turned to neurophysiology and studied motor preparation under risk and uncertainty using TMS alongside TMS' (+EEG, +fMRI) early pioneers (she still finished within three years). She decided to forgo the 2nd PhD degree in philosophy she was offered (twice, at LSE and Groningen University) and came to NYU as a postdoc. While in NYC, she volunteered for data science nonprofit DataKind and, eager to help change people's lives for the better, left academia, was an early Insight Data Science Fellow, and one of the first data scientist at Oscar Health Insurance, a startup born out of the Afforcable Healthcare Act (ACA). She was one of the first to model the consequences of the ACA, and enjoyed being part of a quickly growing billion $ valuation unicorn startup with Karlie Kloss and Ashton Kutcher stopping by. She went on to join a boutique machine learning research and advising company founded by Hilary Mason, a former machine learning professor of data science fame. She now works on applied machine learning problems and advises technical teams at Fortune 1000 companies, from data strategy to technical implementation. She is a frequent public speaker and writer, she continues to volunteer for DataKind and advises the digital innovation unit of the US division of UNRefugees.
Unofficial Story
Friederike got her first job when she was 8 years old as an opera singer in her small German hometown, a job she kept till she graduated high school (wigs are fun). After high school, she moved to The Netherlands not knowing a word of Dutch to study cognitive science, a degree taught in Dutch. She started a second, full time degree in philosophy, lived in a squat, and ran a soup kitchen. A chance internship at the ICN (UCL) gave her a taste of big science and big cities. She could not believe when she was ranked top of her applicant pool and was given a prestigious grant to study neuroscience at UCL (she still wonders if she succumbed to reputation and did not pursue her real passion at the time, philosophy). Disillusionment with science set in during her NYU postdoc, she was looking for a personally more rewarding career with clear impact (and eager to escape competitiveness and other shenanigans). She volunteered for DataKind to try out data science. During a time of upheaval in her lab, when she found herself chased by US Immigrations, she took the plunge and started her career in data science and machine learning. She has endured bro-culture, experienced venture capitalist (VC) entitlement, and would seriously consider turning down a job if they offered daily free lunch. She enjoys that her current career allows her to reinvent herself whenever she wants. She enjoys being surrounded by smart people of varying experiences and educational backgrounds. She still does not know who she wants to be when she grows up. She has learned that optimizing life for happiness is a good deal harder than external approval.