(Repost from 2015) I recently interviewed Hadley Wickham the creator of Ggplot2 and a famous R Stats person. He works for RStudio and his job is to work on Open Source software aimed at Data Geeks. Hadley is famous for his contributions to Data Science tooling and inspires a lot of other languages! I include some light edits. 1.… Continue reading Interview with a Data Scientist (Hadley Wickham)
You have a problem that you think might need some Bayesian modelling A common question I’m asked is how do you start? In this tutorial I take you from a fresh data set, the data set is an educational dataset. I don’t know anything about the data, and I have no specific domain knowledge. I… Continue reading How to build a bayesian model in 30 minutes?
TLDR: This is an opinionated post, but based on recent trends. What is Probabilistic Programming? I recently wrote a course teaching this. Probabilistic Programming is a newish paradigm used in Quantitative Finance, Biology, Insurance and Sports Analytics – it allows you to build generative models to infer latent parameters and the uncertainty of those parameters. It’s been… Continue reading Why Probabilistic Programming is the next big thing in Data Science
On being a Senior Data Scientist This post is partly for myself and based on various peoples conversations – it is also inspired by https://www.kitchensoap.com/2012/10/25/on-being-a-senior-engineer/ I’m trying to answer questions like ‘what do we expect from a Senior Data Scientist’. My job title is ‘Senior Data Scientist’ and I often joke I’ve no idea what… Continue reading What does it mean to be a Senior Data Scientist?
Machine Learning hipster effect Machine Learning is very in vogue at the moment. I feel that a pressure some junior data scientists and engineers feel is the need to do ML just to be a cool hipster, or as a friend of mine calls it ‘the ML hipster trap’. What is the ML hipster trap?… Continue reading Avoiding the ML hipster trap
This is a fairly opinionated post. It doesn’t represent the views of anyone else other than myself. I recently came across – Pitfalls of a non technical manager and it reminded me of some of the things I was talking about in Trophy Data Scientist I recommend the post above, and I’ll give my take on… Continue reading Three pitfalls for non-technical managers managing Data Science teams
Recently I’ve been speaking to a number of data scientists about the challenges of adding value to companies. This isn’t an argument that data science doesn’t have positive ROI, but that there needs to be an understanding of the ‘team sport’ and organisational maturity to take advantage of these skills. The biggest anti-pattern I’ve experienced… Continue reading Avoiding being a ‘trophy’ data scientist
I interviewed the interesting and fascinating Ian Wong – he’s the technical co-founder of OpenDoor, which I personally think is amazing as a concept! 1. What project have you worked on do you wish you could go back to, and do better? Pretty much any project I’ve worked on in the past Two projects stick… Continue reading Interview with a Data Scientist – Ian Wong of OpenDoor
I’ve been in the Data Science space for a number of years now, I first got interested in AI/Machine Learning in 2009 and have a background typical of a number of people in my field – I come from Physics and Mathematics. One trend I’ve run into both at Corporates and Startups is that there… Continue reading Building Full-Stack Vertical Data Products
Jessica Graves is a Data Scientist who currently works on fashion problems in New York City. She’s worked with Hilary Mason at Fast Forward Labs and keeps in regular contact with the London startup scene. After many months of asking her for an interview she finally gave in – and she shares her unique perspective… Continue reading Interview with a Data Scientist – Jessica Graves