Profiting As a Non-Data Scientist

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Because the position is a relative newcomer to the job marketplace, the number of degree programs in data science still lags behind. Colleges and universities are quickly catching onto the trend, however, especially with master’s programs. Today’s data scientists have varied educational backgrounds. Many are former physicists or software engineers who fill the gaps in their skill sets with extra training.

Regardless of previous experience, a candidate for a data scientist job needs, at a minimum, expertise in these areas:

High-Level Math and Statistics – Understanding data structures, modeling, and analysis.
Python – One of the most popular programming languages in data science.
Problem Solving – Understanding the industry you’re working in and which problems are important to solve. Being able to identify ways in which the organization can leverage its data to solve even more problems.
Also important are strong presentation skills, particularly when communicating to iran phone number library non-technical types. You may extract highly meaningful information from customer call data, for example, but if you cannot articulate it in business-speak to the VP of Product, it won’t help the company going forward. Decision-makers should be made to understand what data were used and why, what patterns emerged in the analysis, and what conclusions can be drawn as a result.


Non-technical organizational managers and leaders in data-driven firms are keenly aware of the need to understand the fundamentals of data science themselves. While they don’t have to learn Python coding, they must be able to understand the methodology behind data management in order to ask the right questions, challenge the predictions, and recognize which kinds of problems can be addressed through big data science.

In many fields, proof that you’re competent at making decisions based on data analysis is a must to further your career. Resumes that demonstrate this stand out. Luckily, training programs in this space abound. Fordham University, for instance, hosts a 2-day course entitled “Big Data Analytics for Executives” to teach core concepts of what data scientists do all day. Coursera offers a 1-week online crash course in data science to bring leaders up to speed quickly.

If any of this piques your interest, you may want to explore data science as a profession. If it doesn’t, you may still want to consider taking a high-level overview course on big data analytics. The more you understand how data science can be used to predict outcomes in business, the more you may see how it can help your company. This kind of know-how will soon become all but essential in a professional’s skill set as big data increasingly shapes the way we make business decisions.