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Day in the Life of an Analytics Professional

April 17, 2017

 

What do Analytics Professionals do?

 

In 2017, the website Glassdoor.com ranked the following analytical career fields: Data Scientist #1, Data Engineer #3, and Analytics Project Manager #6. Do college students know what these professionals do on a typical day? There are TV shows with nurses, doctors, police, firefighters and lawyers but there are not any shows that focus on analytics professionals. My challenge over the past few months was to create and deliver a presentation to inform potential future analytics professionals. My presentation title was "A Day in the Life of an Analytics Professional."

 

Over two months, I delivered the presentation to the NC State Sports Analytics and the Math Club, UNC Math Department and finally, during the UNC-Wilmington Cameron Business School Business Week Event. Giving the brief multiple times allowed for refinement and adjustments based on student questions.

 

Walt DeGrange giving the presentation 

 

So what does a typical day look like?

 

 

Research - 10%

Keeping up with the art of the possible is a required daily chore. New methods and technologies are being introduced daily. Assuming a software math solution implemented six months ago is still state-of-the-art is risking irrelevance.

 

 

Coding - 10%

This is the basic skill required for all analytics professionals. As important as the carpenter's tools, coding in various languages such as R, Python, C++, and SAS allows the analytics professional to manipulate and gain insight from data sets.

 

 

Communication - 25%

Communicating with collaborators, clients, project leads, and technical experts is critical to ensure that deliverables are on time and fulfill the requirement.

 

 

Marketing - 15%

Everyone needs to sell. Even the coder that never presents to a client must convince their project lead that their methodology works. This is a very important skill for analytics professionals since many models use math that is not easily understood or explained. These "black box" solutions require a higher level of convincing.

 

 

Project Management - 30%

Keeping analytics projects on track is not like managing a construction project. There are many analysis areas that require familiarization with the data before building a model. Many aspects of model building are more of an art form then a science and thus the time to complete may have a large variation from project to project. One must consider this in the planning and execution of these projects.

 

 

Breaks - 10%

Everyone needs a break, and this is especially true if your job keeps you in front of a computer screen. Walking, running, and cycling give me time and space to think about challenges. Sometimes your unconscious mind needs this distraction to develop solutions. Plus the physical exercise is good for you.

 

Of course, this is just a sample day. Why I love analytics is that I can apply the techniques across many industries and solve a multitude of challenges. This results in schedule variation every day. Also, my role these days falls more on the project management side. I would guess a technical analytics professional would spend 30% or more of their time coding and less on project management.

 

Overall, the feedback from the students was positive. Many students were glad to learn about what to expect if they choose an exciting career in analytics.

 

If you would like to take a look at the brief, it is available at https://www.slideshare.net/ltwalt/day-in-the-life-analytics-professional

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