10 Key Tips for Entry-Level Analytics Professionals

With so many companies hunting down the data scientist. There are few things which aspirants can do to increase their chances of being getting selected into the best ones.

By Katie Ferguson (@BurtchWorks).

It’s no secret that analytics and data science are the hottest fields to get into right now. But getting into the field can be tough, and even with a stellar degree it can be tricky to navigate the quantitative job landscape as an entry-level professional. Here at Burtch Works we’ve worked with many great clients, and have developed a checklist of things they look for in early career professionals, as well as tips that may help you in your initial search.


1. Complete an internship – A great way to test your skills, continue learning, and expand your network is to complete an internship. Without previous work experience, prospective employers will look at internships (as well as coursework) to determine if you might be a good fit for their organization.

2. Get experience with large, real-world data sets – One of the biggest challenges students will face in their first analytics job is their lack of experience with messy, large, real-world data sets. It is crucial that you find a way to add this to your experience, either through MOOCs (massive online open curriculum) such as Coursera or Udacity, internships, coursework, or Kaggle competitions.

3. Try Kaggle competitions – Kaggle hosts data crunching competitions where you can practice your skills, compete against other members, and gain access to large, real-world data sets similar to the ones you might use at your first job. It is a great resource, and employers often view Kaggle experience similar to how they would view coursework or internships.

4. Get a SAS certification – Although the availability of tools to wrangle Big Data has been diversifying, many employers still use SAS, and many look to the certification to verify credibility of analytical skills. Even though, according to our recent SAS vs. R flash survey, R has been gaining in popularity among analytics professionals and is especially preferred among data scientists, a SAS certification can still add credibility to your resume.

5. Create a complete LinkedIn profile – Over 90% of recruiters who recruit using social media use LinkedIn. It has become the go-to resource for many companies to check your references and resume, and having an updated, professional profile allows companies to see you as a person they might want to hire, not just an anonymous resume.

6. Look into an advanced degree – In our Burtch Works Study: Salaries of Predictive Analytics Professionals report last year we discovered that 86% of analytics professionals have at least a Master’s degree, and 18% have a Ph.D. In data science, 88% of data scientists hold at least a Master’s degree, and 46% have a Ph.D.

7. Familiarize yourself with the industry – Learn about the key players in your industry, what the latest tools and techniques are, and stay aware of industry news that may affect your opportunities or the companies you’re applying to.

8. Research companies – As well as knowing more about the industry you’re targeting, you should make sure to research the companies you’re applying to. Knowing about changes in business strategies, corporate goals, and current events are all ways to show that you have business savvy as well as technical chops. Companies like to hear that you are well-informed, because this shows that you are committed, interested, and willing to learn as much as you can about their needs and concerns.

9. Read job descriptions – Looking through job descriptions is a great way to get a feel for what technical skills companies are looking for, and can help inform what else you may need to learn. You may learn that the companies you’re applying to are all looking for certain tools like R, SQL, Python, etc. and can look for online resources to learn those skills.

10. Network, network, network! – Although it may be daunting, networking is a great way to learn about new opportunities. Check out your local chapter of the ASA, join other industry groups, or attend local meetups to network with professionals in your field and industry. Once you have completed your LinkedIn profile, you can also add everyone you meet as connections and join relevant LinkedIn groups.

For more information about job interviews, references, and strengthening your communication skills, check out our Young Analytics Professionals series of white papers. And check out the Burtch Works blog for posts like the biggest job search mistakes and biggest career strategy mistakes we see quantitative professionals making, as well as our take on current events in analytics and data science. Best of luck with all your endeavors, and make sure to connect with us on LinkedIn!

Katie FergusonBio: Katie Caplis Ferguson is an analytics specialist at
Burtch Works
recruiting agency.

Original. Reposted by permission.