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How to Become a Data Scientist

CAREER GUIDE

How to Become a Data Scientist

Data science is one of the most exciting fields for computer scientists and statisticians today. This rapidly expanding field is one of the newest STEM career paths of the 21st century, yet it is already an essential position in almost every major business. Not only are data scientists in high demand but they are well compensated for their work. Here we will take a look at what data science is, the requirements to work in this field, and the benefits that come from this career path. 

Here are a few reasons to consider a career in data science:

According to the US Bureau of Labor Statistics, the information and computer science field is projected to grow over 16% over the next ten years.

There are over the 12,000 jobs currently posted for data scientists at Indeed.com in the US alone.

Data science is one of the highest paying entry-level tech careers.

12000
Listings
124567
Average Salary
1500
Hiring Companies

Data science is adjacent to computer science. While much of what both fields do overlap, data scientists have a focus on the analysis of data, while computer scientists have a general focus on computers. Like many other tech fields, these titles are nebulous and often do similar work. 

 

Data science is a new term, having been first coined around 2008 as more and more companies have begun to see the value in big data and data analysts in general. Big data is a term referring to the volumes of valuable information that have become available to many companies. For example, Google receives billions of searches per day. Studying what people search for can help companies determine what’s happening in their market, customer pain points, and other valuable information. 

What do Data Scientists Do?

Data scientists work with high-level algorithms, artificial intelligence, and other computer software. Most data scientists have mastery over at least one programming language that they use regularly, though many are well versed in more than multiple languages and tools. 

Data Science Job Description

Data science brings computer science fields that study data like statistics, data analysis, and machine learning under one data themed umbrella. Data scientists use advanced analytics and predictive models to derive or produce useful information from an often large and endless stream of structured and unstructured data sets. Their priority is producing results that can be understood by nontechnical teams to improve various aspects of a company, from sales to safety.

Managing databases

Interpreting large data sets

Analyzing data and transforming it into useful business guidelines

Data mining

Database expansion and modernization

Staying informed with the latest big data breakthroughs

Data science is a challenging field that requires a sharp, analytical mind and a love of data. Like many science fields, it certainly isn’t for everyone. If you have a love of statistical math, complex puzzles, computers, and finding patterns in static then you might have an inclination for data science. 

 

However, data scientists aren’t only data driven; they require good critical thinking to turn statistical analysis into useful real-world concepts (we should drop the price of our product, or color our product blue). In addition, they need excellent communication skills to convey the results of their work to the rest of their team or company. 

Data scientists must learn and practice a wide range of skills, programming languages, and more. With any of the above methods used to enter the field, these are the skills that every data scientist should have in their back pocket.

Math and statistics

Almost any computer science field requires a good handle on math. Computer scientists need to be math experts. Understanding statistical functions and using algorithms to wrangle data are critical skills in computer science.

Tools, frameworks, and programming languages

R and Python are among the most popular programming languages for machine learning and data analysis. Other frameworks and tools include SQL, Hadoop, TensorFlow, scikit‑learn, and NumPy among others.

Analytical and logic skills

Using the above to get a final number is only half the battle. Data scientists need to create an analysis that will produce useful information in the first place, and then figure out what that information actually means for a company in the real world. Doing this requires critical thinking and good analytical skills.

Interpersonal skills

It’s one thing to derive a meaningful result out of a pool of data, and another to accurately explain what that result means to a group without a statistical or computer science background. Turning raw results into a clear directive that can be handed out to shareholders and marketing executives is a part of a data scientist’s job.

Data scientists are fantastically compensated. According to Glassdoor, junior data scientists without any experience earn an average base salary of $73,645, with an average cash compensation (bonuses, commission, and profit-sharing) that bring the total number up to over $80k per year.

CityAverage Salary
Atlanta, GA$101,183
Boston, MA$110,373
Chicago, IL$102,543
Cleveland, OH$93,282
Dallas, TX$100,556
Los Angeles, CA$116,447
Miami, FL$100,699
Milwaukee, WI$95,749
Minneapolis, MN$95,558
New York, NY$113,156
Philadelphia, PA$97,921
Phoenix, AZ$102,489
Portland, OR$120,664
San Francisco, CA$140,897
Seattle, WA$125,692

Data scientists play an essential and complex role in the tech industry. As a result, these professionals earn high salaries across the country.

  • Mean Annual Salary: $124,567
  • Projected Job Growth Outlook (2018-28): 16%
  • Number of People Employed: 140,000
  • Mean Annual Salary: $88,280
  • Projected Job Growth Outlook (2014-24): -7%
  • Number of People Employed: 273,600

Programmers write and test code to ensure that computer applications and software programs function as they should. They work with plans formulated by software developers and engineers and turn them into instructions for computers.

  • Mean Annual Salary: $98,350
  • Projected Job Growth Outlook (2014-24): 28%
  • Number of People Employed: 100,000

Information security analysts create plans to protect an organization’s computer networks and systems. They are the first line of defense against cyberattacks.

  • Mean Annual Salary: $90,070
  • Projected Job Growth Outlook (2014-24): 11%
  • Number of People Employed: 119,500

DBAs work with special software to store and organize a company’s important data. They ensure the data is organized, accessible by authorized individuals, and safe from unauthorized access.

Data scientists use programming languages such as Python to manage and interpret large volumes of data.

PositionSalary
Entry Level (0-4 Years)$80,000
Mid-Career (5-10 Years)$125,000
Experienced (10-20 Years)$150,000
Late-Career (20+ Years)$200,000

In general, data scientists have an average enticing compensation rate (cash compensation included) of $124,567. Senior data scientists earn even more with an average compensation of $146,937. If these numbers look good, then all that is left is to figure out how to get from point A to point B.

The Types of Data Scientist

As data becomes more and more important to nearly everyone, there is an increasing number of roles that are data specific. Let’s briefly compare the top three positions with data in the title:

Data Analyst

A data analyst uses existing methods and algorithms to analyze data, and produce useful and practical results for their employer. They are well versed in the tools and methods used for handling and studying data and focus on what the data means.

Data Engineer

Data engineers build the systems and algorithms that data analysts use for data visualization and study. They are experts at manipulating data with production-ready software and focus on how data should be handled and measured.

Data Scientist

Data scientists do all of the above. They are not only experts at analyzing and interpreting data, but at building custom algorithms for their company’s specific needs. They still focus on interpreting the meaning of data, but they also have the ability and understanding to organize data in their own programs and algorithms.

Like many job fields, there are multiple ways to enter and succeed in the data scientist job field. Here we will look at the possibilities and weigh the pros and cons of each.

With a Master’s in Data Science

A master’s degree in computer or data science is considered the traditional route into any computer science field, data science included. A master’s degree in the field is listed as a requirement on many job listings and is considered the standard education requirement by the BLS. With a master’s in the field you will probably come up near the top in the stack of resumes viewed by any hiring manager. 

 

While a master’s degree will provide the foundation and essential math skills for a career in data science, data science is a new field. Many educational institutions do not have a course that effectively prepares students for this field specifically. In addition, Master’s degrees are lengthy and expensive. They often take six years of full-time study to complete (starting with just a high school education) and cost tens of thousands of dollars. 

 

In addition, a degree is only education, not experience. The real-world problems encountered in the field may not match up to what you’ve learned, and without any internship experience, a degree holder may still have trouble when putting what they’ve learned into practice. 

With a PhD in Data Science

According to a 2019 study from Burtch Works 44% of Data Scientists hold a PhD. A doctorate is the highest level of collegiate education, and having one will put you at the top of any hiring manager’s to hire list. However, getting a PhD in data science takes even more money and time than getting a master’s. In addition, those with a PhD still do not necessarily have any work experience, and still might not be totally prepared for the realities of working in the field. 

MOST COMMON

Coding Bootcamps

Coding bootcamps arose out of necessity. These programs, which became popular in the last decade, can be a fast-track route into a software engineering career. Bootcamps, like colleges, cover a wide range of programming languages and computer science skills. However, unlike college, they skip general education and get right down to in-demand skills for your chosen career path. Bootcamps last between three months and one year. These programs are available for software engineering, web development, application development, project management, cybersecurity, financial technology (FinTech), and more. On average, bootcamps cost around $13,000 for a full-time and full-length curriculum.  

  • Duration: 1 to 5 years
  • Cost: $0 (or minimal)
  • Average Base Salary: Unknown
  • Duration: 3 to 12 months
  • Cost: Avg. $13,600
  • Average Base Salary: $70,700
  • Duration: 4 to 6 years
  • Cost: Avg. $34,740 (4 years)
  • Average Base Salary: $65,900
  • Duration: 1.5 to 2 years (in addition to Bachelor’s Degree)
  • Cost: Avg. $30,000 to $100,000 (in addition to Bachelor’s Degree)
  • Average Base Salary: $114,000
  • Duration: 4 to 8 years (in addition to Bachelor’s Degree)
  • Cost: Avg. $50,000+ (in addition to Bachelor’s Degree)
  • Average Base Salary: $124,000

Coding Bootcamp

Coding bootcamps are fast, intensive career training programs that focus on job placement and in-demand skills. Software engineering bootcamps cover coding languages such as HTML, JavaScript, Python, Ruby, and more. Bootcamps don’t focus on general education, and some offer job placement guarantees with employment rates of over 90%. Thanks to high demand for qualified engineers, bootcamps became a proven route into a high-paying tech career.

College/University

Traditional colleges, universities, and graduate schools offer the prestige of a degree and a high-quality education. Students often earn a bachelor’s degree in computer science before landing a tech job. In fact, many positions list a degree as a requirement, but this isn’t always the case anymore. Students can apply for colleges after high school, and graduate school to earn a master’s degree in computer science.

Self-Study

Thanks to a wealth of information on the internet, some people manage to train themselves to become software engineers without attending school. It’s true that these self-taught programmers occupy high-paying positions within top companies. However, most people benefit from attending school, as coding is a complex task that often puts people off when they get stuck.

FAQ

How long does it take to learn data science?

It depends on the education path you choose. Bachelor’s degree programs take four years, but coding bootcamps take less than a year to complete.

Do you need a degree to become a data scientist?

Not necessarily. People without any college education can become data scientists, but most professionals have a bachelor’s degree.

Is data science a good job?

For many people, data science is an excellent job. The work is fulfilling, and the job pays extremely well.

Can data scientists work from home?

Yes! Data scientists can work from home as freelancers or remote employees.

How much do web developers make?

The average salary for web developers is $124,000 per year. Salaries range from $80,000 to $200,000 per year. 

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