Starting a career in data science

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.

Regards,
Aran

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The hidden benefits of open-source software

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 →

ODI looking for young postgrad statisticians

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.

Essential criteria:

  • 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.

Read some first-hand experiences of current and former Fellows.

 

ABS seasonal adjustment update

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.

Now that the ABS has put out a statement about the problem, I thought it would be useful to explain the underlying methodology for those who are interested. Continue reading →

Explaining the ABS unemployment fluctuations

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 →

Connect with local employers

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.

Now the local organizers are going to extend the opportunity to allow job-searchers to give a 90 second pitch to employers. Details are provided on the message board.