This post is contributed by Katie Ferguson and Flora Jiang, Burtch Works’ early career recruiting experts.
If you’re completing your Master’s degree or PhD and looking to break into the analytics field, you’ve no doubt heard about how hot the market is for predictive analytics professionals right now. One need only glance over this article with an analysis from the American Statistical Association to see that more students are earning statistics degrees, and that number will undoubtedly continue to increase as more schools expand their programs to meet the demand for analytics professionals and data scientists.
With increasing competition for junior-level positions, it will become even more important to set yourself apart from the other candidates, and one of the best ways to do that is by completing an internship. At Burtch Works we’ve worked with many early career analytics professionals, which has given us a unique insight into what employers are most looking for in recent graduates: experience with real-world data and the ability to adequately explain technical findings.
As a student, many of the data sets you come into contact with are created as samples and are therefore relatively clean compared to “real world” data sets. Many recent grads often have difficulty when they enter their first job and realize that the data they will be working with is much messier and more complex than what they had experience with at school. One of the benefits of an internship is the ability to work with data sets that were not created as practice sets, and are therefore much closer to what you will be working with on the job.
Some other benefits of internships, and criteria that you should look for when choosing one are:
- Working on a project from start to finish
- Practicing manipulating very large datasets using SAS, SQL, or other tools
- Opportunities to practice presenting your findings
- The ability to make an impact that you can put on your resume
In addition, internships offer fantastic mentorship and networking opportunities, and you may get hired by the company at the end of the internship. Even if you aren’t hired by the company at the end of the internship, the professionals you work for at the internship can make excellent job references in your upcoming job search because they’ve seen you at work, rather than a professor recommending you based on your performance in an academic environment.
Some of the downsides to completing an internship are that it can take away from your schoolwork and some of them are unpaid. Working on your degree should be your priority, but if you’re in the position to take an internship opportunity the experience will be very helpful. Recent grads who’ve had internship experience also tend to perform better in interviews, and are more polished than those without internship experience.
So where can you find an internship? Although Burtch Works doesn’t work with internships, sites like Indeed, Icrunchdata, and your local ASA chapter are all good places to look, as well as relevant LinkedIn groups, your university’s career center, and your professors. If you’re unable to work on an internship, an academic corporate project that utilizes real-world data or Kaggle competitions can be other ways to bolster your experience with large, messy datasets. This article has a few more tips for early career analytics professionals.
Interested in our salary research on data scientists and predictive analytics professionals? Download our studies using the button below.
Want to learn more about data science and analytics career planning? Watch the webinar recording below to hear our recruiters’ best advice on interview preparation, tools and skills to learn, salaries, and more!