I am data scientist with product management background and passion for machine learning and financial data. My background is in behavioral science, statistics and human-computer interaction. I worked in venture capital and completed the Data Incubator bootcamp. I work in R and Python, see GitHub. I am particularly interested in:

  • learning at low false positive rate
  • fraud detection / anomaly detection
  • data visualization using RShiny, plot.ly, ggplot2
  • experimental design and evaluation with robust methods (e.g. mixed effects modelling with lme4)
  • algorithmic trading of indices, crypto currencies and arbitrage using machine learning

investments / board memberships

stuff I worked on

  • b2b credit scoring (e-commerce)
  • crypto currency prediction & arbitrage
  • stock index prediction & backtesting
  • key-account / lead prospecting
  • subscription payment APIs
  • SalesForce.com implementation
  • focus.ly: prototype of distraction-blocking software Based on research on multi-tasking by Stanford professor Clifford Nass

publications, conferences & workshops