At the end of April 2017, I will leave my university job and start freelancing. I will be offering training and analysis, focusing on three areas:
- Health research & quality indicators: this has been the main applied field for my work with data over the last nineteen years, including academic research, audit, service evaluation and clinical guidelines
- Data visualisation: interest in this has exploded in recent years, and although there are many providers coming from a design or front-end development background, there are not many statisticians to back up interactive viz with solid analysis
- Bayesian modeling: predictive models and machine learning techniques are big business, but in many cases more is needed to achieve their potential and avoid a bursting Data Science bubble, and this is where Bayes helps to capture expert knowledge, acknowledge uncertainty and give intuitive outputs for truly data-driven decisions
Considering the many “Data Science Venn Diagrams”, you’ll see that I’m aiming squarely at the overlaps from stats to domain knowledge, communication and computing. That’s because there’s a gap in the market in each of these places. I’m a statistician by training and always will be, but having read the rule book and found it eighty years out of date, I’m have no qualms in rewriting it for 21st century problems. If that sounds useful to you, get in touch at email@example.com
This blog will continue but maybe less frequently, although I’ll still be posting a dataviz of the week. I’ll still be developing StataStan and in particular writing some ‘statastanarm’ commands to fit specific models. I’ll still be tinkering with fun analyses and dataviz like the London Café Laptop Map or Birdfeeders Live, and you’re actually more likely to see me around at conferences. I’ll keep you posted of such movements here.