I keep telling students that there are lots of jobs in data science (including statistics), and they often tell me they can’t find them advertised. As usual, you do have to do some networking, and one of the best ways of doing it is via a Data Science Meetup. Many cities now have them including Melbourne, Sydney, London, etc. It is the perfect opportunity to meet with local employers, many of which are hiring due to the huge expansion in the use of data analysis in business (aka business analytics).
At the end of each Melbourne meetup, some employers have been advertising their current analytic job openings to the audience.
Next week, Professor Di Cook from Iowa State University is visiting my research group at Monash University. Di is a world leader in data visualization, and is especially well-known for her work on interactive graphics and the XGobi and GGobi software. See her book with Deb Swayne for details.
I’m about to head off on a speaking tour to Europe (more on that in another post) and one of my hosts has asked for my powerpoint slides so they can print them. They have made two false assumptions: (1) that I use powerpoint; (2) that my slides are static so they can be printed.
Instead, I produced a cut-down version of my beamer slides, leaving out some of the animations and other features that will not print easily. Then I produced a pdf file with several slides per page. Continue reading →
Unlike most of my talks, this is not intended to be primarily about my own research. Rather it is to provide a state-of-the-art overview of the topic (at a level suitable for Masters students in Computer Science). I thought I’d provide some historical perspective on the development of automatic time series forecasting, plus give some comments on the current best practices. Continue reading →
I am teaming up with Revolution Analytics to teach an online course on forecasting with R. Topics to be covered include seasonality and trends, exponential smoothing, ARIMA modelling, dynamic regression and state space models, as well as forecast accuracy methods and forecast evaluation techniques such as cross-validation. I will talk about some of my consulting experiences, and explain the tools in the forecast package for R.
The course will run from 21 October to 4 December, for two hours each week. Participants can network and interact with other practitioners through an online community. Continue reading →
When I want to insert figures generated in R into a LaTeX document, it looks better if I first remove the white space around the figure. Unfortunately, R does not make this easy as the graphs are generated to look good on a screen, not in a document.
I’m speaking on this topic at the Young Statisticians Conference, 7–8 February 2013.
If you’re a young statistician and live in Australia, please book in. It promises to be a great couple of days. Early registrations close on 2 January.
Abstract for my talk:
For 25 years I have been an intrepid statistical consultant, tackling the wild frontiers of real data, real problems and real time constraints. I have faced problems ranging from linguistics to river beds, from making paper plates to selling pies at the MCG, from tax office audits to surveys about the colour purple. University education helps prepare you to be a statistical consultant in the same way that Google maps helps prepare you to cross the Simpson Desert. You have some idea of the main features, but when you get there, nothing looks familiar.
I will describe some of my adventures, and explain how to bluff your way through ignorance, work with inadequate tools, and deal with smelly clients. I will tell you the story of the client who wouldn’t give me the data, the client who wouldn’t tell me the problem, and the client who wanted all meetings held at random locations for security reasons.
Along the way we will learn about the skills that statisticians need to survive in the wild.