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Resume Tips for Early Career Analytics Professionals


Trying to put together your first resume or two after graduation can be tricky. Without a lot of relevant work experience to highlight, sometimes none at all, graduates often wonder how they can adequately impress hiring managers with their analytics capabilities.



By Katie Ferguson and Flora Jiang, Burtch Works.

This post is contributed by Katie Ferguson and Flora Jiang, Burtch Works’ early career recruiting experts.resume meme

Trying to put together your first resume or two after graduation can be tricky. Without a lot of relevant work experience to highlight, sometimes none at all, graduates often wonder how they can adequately impress hiring managers with their analytics capabilities. There are also increasing numbers of fresh graduates vying for each position, in addition to professionals from other fields making a career transition.

How can you make sure your resume gets noticed? In our experience working with early career analytics professionals, such as those who’ve recently completed their Master’s in Statistics or who have only held one position in industry, here are the things that hiring managers are looking for in a resume:

1. List of technical skills – Include a list of your technical skills (SAS, R, Python, SQL, etc.) in a place that is easy for the hiring manager to find. Make sure that every tool or technical skill you list is supported somewhere on your resume. It is not enough to simply have a list of tools that you use. Either in your work, internship, or project experience you should mention how you used each one.

2. Actionable bullets to support each position – For bullets to communicate your experience effectively (whether that is work, a personal data project, or internship experience) they must be actionable. This means that they show an objective, how you worked towards that objective, the outcome of the project, and your personal impact on the project. Make sure that all of your bullets use the same verb tense.

3. List education and relevant coursework – Especially if you don’t have relevant work experience, listing out your education and coursework is the best way to give your potential employer an idea of what areas you studied. If you used specific tools in each class, those should be included here.

4. Internship or project experience – We’ve written previously about the importance of internships for analytics students, one of the main reasons being that employers want to see if you have experience with real, messy datasets. Keep this in mind when describing your internship experience. If you weren’t able to complete an internship, you can also use a school or personal data project as an applicable example.

5. Proper format – Resumes for early career analytics professionals should be limited to one page and contain no spelling or grammatical errors. Use a professional email address.

6. Extracurricular data projects – Hiring managers are always interested to see quantitative professionals who have completed related passion projects. Have you completed a few Kaggle competitions? What about creating a data-driven approach to your fantasy football team or March Madness bracket? These are all great examples of personal data projects that employers will be interested in hearing about! They show your breadth of experience and, most importantly, that you are very passionate about data.

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