Top 3 Foundational Skills of a Data Scientist
Individuals in this profession generally have an operational understanding in the foundational data-science skills of programming, math, and the industry in which they work.
Programming is a key component of the typical data-scientist skillset. A career that starts in programming provides an excellent foundation to become a data scientist — hacking skills can be directly applied to data analysis.
Advanced math is another core skill needed to become a data scientist. Great analyst and development teams have mathematicians (i.e., quants), so developing applied math skills enables you to work as a key contributor on the team.
3. Industry Expert
Fancy programming and quantitative analysis is worthless without context — the industry expert on the team provides this expertise. Each industry has unique attributes that require specialization. For example, healthcare is very different from public policy which are both different from finance.
Solidifying Skills and Gaining Experience with a Master’s in Data Science.
Each foundational skill mentioned puts you on a path to become a data scientist who has a fusion of all three skills: programming, math, and expert-level industry knowledge. If you are a hacker, a quant, or an industry expert who’s focused on analysis, you are on a path to be a data scientist; but many people still need to further their skills and experience.
In applied fields like data science, you expand your skills and learn by doing, be it in practical coursework in a Master’s in Data Science program, or on the job by applying expertise to team projects. This requires iterations, with failure as much as successes, mentorship, and constant learning.
Gaining on-the-job training (OJT), while great in that you learn with your team and expand your skill set to include all the foundational skills, is often limited or not available at all, and for different reasons. Companies need someone who has shown time and again they understand how to leverage the information. So, while you can watch the “pros” do it, you don’t gain the experience or knowledge directly, and may only “learn” through partial information. And then, to the opposite extreme, sometimes an organization simply does not prioritize analysis, so opportunities to expand your data science skills are limited.
However, earning a master’s degree in data science in an experiential program like that of Utica College demands you apply what you learn immediately to real-life scenarios, and overcomes both obstacles. First, it delivers direct experience in all the key skills, allows a deeper understanding of how to think about data, enables experimentation with software and techniques, and provides mentorship with networking opportunities. Throughout your coursework, you will become an experienced expert. Additionally, when you understand and can quantify how data science can be used to benefit an organization, you can make a strong case for data science and its technology to be used as the basis of decision-making.
Determine Your Path to Become a Data Scientist — Consider a Master’s Program
The methodology outlined to become a data scientist relies on dedicated practice and coaching, mentoring and instruction. This is how you become an expert at anything. To gain skills, experience, mentoring and access to a professional network quickly, consider the online Master’s in Data Science program at Utica College.
You can learn more, or call and speak with an admissions advisor at 315.732.2640 or toll free when you call 866.295.3106.