How to become a data scientist

Tim Jonas our consultant managing the role
Author: Tim Jonas
Posting date: 6/28/2018 3:10 PM

Looking to ramp up your career prospects in 2018? Then consider data science. As a Data Scientist, you’ll be filling a much needed role for businesses industry-wide and will be in what a recent article called “this century’s hottest career”. 

Last week, in the first of our 2-part series, we talked about how employers find and retain top data science talent. In this article, we’ll focus on how prospective employees can improve their chances in the market.

As the year comes to an end, revenue growth is expected to double for a third of Fortune 500 companies. But, it’s not just the big boys who’ll need Data Scientists and be growing data science teams. More often than not, you’ll be more likely to get your foot in the door through one of the millions of startups and small to medium businesses. In San Francisco, one of the hiring hotspots for data professionals, 65% of businesses are startups less than eight years old. 

Basic Skills and Tools

While degrees both undergrad and higher education abound, close inspection of job descriptions requires at the least a bachelor’s degree for aspiring and junior level professionals. Advanced positions may require advanced degrees, though the basics and experience count a bit higher. Application of theory is key, so knowing the basic skills help to set up a solid foundation on which to build a career.

Python, R, and SQL; nope, it’s not an eye chart. These are a few of the basic statistical programming language you’ll need to know. In addition to these languages, a knowledge and understanding of basic statistics; while useful in machine learning applications, it can also help define, design, and evaluate experiments for decision makers. And last, but not least, a solid grasp of linear algebra and multivariable calculus, round out the basics of a data science skills toolbox. 

But, what to do with all that data; how do you translate it to explain customer behaviors and how the customer experience can be improved upon? A data scientist who can crunch the numbers, then tell a story is the penultimate employee for any business. It’s this disparate combination which has led to the creation of data science teams. 

Tell Me a Story

Knowing complex math, statistics, algorithms, and computer languages are basic components of data science, but how do you explain your findings to the decision makers. Companies need data-driven problem solvers, but translating analysis requires a different type of thinking. 

Think beyond the numbers and consider what is important to the company to help them test an idea or develop a new product. What isn’t important? How should you interact with your team? What about those outside your team such as engineers or product managers? Knowing the kinds of questions to ask and understanding the business can help guide how information is communicated. 

The ability to communicate for both technical and non-technical audiences is the next step in the process to improve your chances in the market. Data Scientists who can describe their findings and how various techniques work; help decision makers visualize the data as well as the principles behind the information. 

Looking Ahead

In 2011, the McKinsey Global Institute (MGI) report estimated a shortfall of data scientists in the U.S. of between 140,000 and 190,000 by 2018. As we approach 2018, it is now estimated millions of people will be needed to translate data scientist’s work to the organization. Though it’s been suggested that domain experts obtain data analysis knowledge to act as translators, a data scientist with a deep knowledge of their company and its business, who can translate their findings, will be a boon to their organization.

If you’ve set a new year’s resolution goal to raise the bar on your career and are interested in big data, check out our current vacancies here. Harnham specialize in Data and Analytics recruitment and have opportunities at both junior and senior levels. 

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