Eyal Kazin איל קאזין
Ex-cosmologist turned data scientist with over 15 years experience in solving challenging problems. I am motivated by intellectual challenges, highly detail oriented and love visualising data results to communicate insights for better decisions within organisations.
My main drive as a data scientist is applying scientific approaches that result in practical and clear solutions. To accomplish these, I use whatever works, be it statistical/causal inference, machine/deep learning or optimisation algorithms. Being result driven I have a passion for facilitating stakeholders to make data driven decisions by quantifying and communicating the impact of interventions to non-specialist audiences in an accessible manner.
My claim for fame is that between 2004-2014 I lived in four different continents within a span of a decade, including three tennis Grand Slam cities (NYC, Melbourne, London).
Sessions
In hypothesis testing the stopping criterion for data collection is a non-trivial question that puzzles many analysts. This is especially true with sequential testing where demands for quick results may lead to biassed ones. I show how the belief that Bayesian approaches magically resolve this issue is misleading and how to obtain reliable outcomes by focusing on sample precision as a goal.