We are hiring again, and looking for people in statistics, econometrics and related fields (such as actuarial science, machine learning, and business analytics). We have a strong business analytics group (with particular expertise in data visualization, machine learning, statistical computing, R, and forecasting), and it would be great to see it grow. The official advert follows.
One of the great services of the Statistical Society of Australia is an excellent jobs board advertising available jobs for statisticians, data analysts, data scientists, etc. Jobs can be filtered by industry, location and job function.
Today the SSA announced a new service to job seekers: CV/Resume Critique. Continue reading →
I received this email from one of my undergraduate students:
I’m writing to you asking for advice on how to start a career in Data Science. Other professions seem a bit more straight forward, in that accountants for example simply look for Internships and ways into companies from there. From my understanding, the nature of careers in data science seem to be on a project-to-project basis. I’m not sure how to get my foot stuck in the door.
I am expecting to finish degree by Semester 1 2016. In my job searching so far, I have only encountered positions which require 3+ years of previous data analysis experience and have not seen any “entry-level” data analysis positions or graduate data positions. What is the nature of entry level recruitment in this industry?
Any help would be greatly appreciated.
I’ve been having discussions with colleagues and university administration about the best way for universities to manage home-grown software.
The traditional business model for software is that we build software and sell it to everyone willing to pay. Very often, that leads to a software company spin-off that has little or nothing to do with the university that nurtured the development. Think MATLAB, S-Plus, Minitab, SAS and SPSS, all of which grew out of universities or research institutions. This model has repeatedly been shown to stifle research development, channel funds away from the institutions where the software was born, and add to research costs for everyone.
I argue that the open-source model is a much better approach both for research development and for university funding. Under the open-source model, we build software, and make it available for anyone to use and adapt under an appropriate licence. This approach has many benefits that are not always appreciated by university administrators. Continue reading →
The Overseas Development Institute Fellowship Scheme sends young postgraduate statisticians (and economists) to work in the public sectors of developing countries in Africa, the Caribbean and the Pacific on two-year contracts. This is a great way to develop skills and gain experience working within a developing country’s government. And you get to live in a fascinating place!
The application process for the 2016-2018 Fellowship Scheme is now open. Students are advised to apply before 17 December 2015 for a chance to be part of the ODI Fellowship Scheme.
- degree in statistics, economics, or a related field
- postgraduate degree qualification
- ability to commit to a two-year assignment
Application is via the online application form.
We are now advertising for various positions in applied statistics, operations research and applied mathematics.
These jobs are with MAXIMA (the Monash Academy for Cross & Interdisciplinary Mathematical Applications).
Please do not send any questions to me (I won’t answer). Click above and follow the instructions.
Since my last post on the seasonal adjustment problems at the Australian Bureau of Statistics, I’ve been working closely with people within the ABS to help them resolve the problems in time for tomorrow’s release of the October unemployment figures.
I do not normally post job adverts, but this was very specifically targeted to “applied time series candidates” so I thought it might be of sufficient interest to readers of this blog. Continue reading →
Although the Guardian claimed yesterday that I had explained “what went wrong” in the July and August unemployment figures, I made no attempt to do so as I had no information about the problems. Instead, I just explained a little about the purpose of seasonal adjustment.
However, today I learned a little more about the ABS unemployment data problems, including what may be the explanation for the fluctuations. This explanation was offered by Westpac’s chief economist, Bill Evans (see here for a video of him explaining the issue). Continue reading →
It’s not every day that seasonal adjustment makes the front page of the newspapers, but it has today with the ABS saying that the recent seasonally adjusted unemployment data would be revised.
I was interviewed about the underlying concepts for the Guardian in this piece.
Further comment from me about users paying for the ABS data is here.