Our BLOG

How To Break Into Data Science

Share it
Facebook
Twitter
LinkedIn
Email

In May 2023 Springboard.com reported there has been a 480% increase in data science job openings since 2016 and Glassdoor lists data science as its third-best job in America. Surprisingly, you don’t have to have an advanced degree in statistics to become a data scientist, but there are a number of basic requirements. Do you have what it takes to break into data science?

The Bare Minimum

You must have an affinity and an ability to utilize statistics and computer skills to address key business challenges. In other words, it isn’t enough to be a math and computer whiz, you must have an interest in applying those skills to answering specific problems within your organization.

Masters in Statistics NOT Required

While making a break into data science with a masters in statistics might be easier, you don’t have to start there. You must have foundational math and statistics skills that can be acquired a variety of ways. Perhaps you started out as a data analyst cleaning and preparing data for your associate or manager data scientist. Interfacing with analytical experts is one avenue to advance your mathematical skills. An undergraduate degree in statistics, math or computer science also works. Internships and project work in applying statistics to build predictive models or conduct research can give you hands on skills hard to find outside of a data science job. Moving on from regression modeling to machine learning and natural language processing with a good analytical foundation will accelerate your data science career.

Programming to Break Into Data Science

While you might have data management and preparation support from a data analyst and more sophisticated IT support from a data engineer, you must have some SQL skills to work in the variety of databases that you will see. You must be extremely strong in Python or R to break into data science. Some industries like pharmaceuticals and banking and credit use SAS as well. These last three languages, Python, R and SAS, are much easier to learn and apply. Bootcamps can get you started and then there are many free datasets that you can use to practice on. Build a personal portfolio of work you have done using one or two of these computer languages.

Here’s How You Excel

Most data scientists are attracted to this career because of their interest and enthusiasm for applying their analytical and computer skills to data. Real success in a data science career comes from knowing how to apply those skills to answer specific business problems and then being able to COMMUNICATE those results and solutions to non-technical leadership in your organization. Yes, becoming a master at using data visualization tools helps in this process, but it is the insight you bring to the analysis and the ability to communicate how your work offers an answer to their problem that wins the day, and proves your value to the organization.

Interested in hiring a data scientist or discussing your data science career? Contact Smith Hanley Associates’ Data Science and Analytics Recruiter, Paul Chatlos at pchatlos@smithhanley.com

Share it
Facebook
Twitter
LinkedIn
Email

Related Posts

PMSA Annual Conference Recap

WOW! What a conference! The 2024 PMSA Annual Conference delivered on pharmaceutical industry advanced commercial analytics content and training, on industry professionals to network with

Read More »
artificial intelligence ethics

Artificial Intelligence Ethics

Artificial Intelligence (AI) is not just transforming industries; it’s reshaping the ethical landscape of our digital world. As AI systems become more integrated into our

Read More »