Data Scientist

Portland, OR, United States

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How to Become a Data Scientist CAREER GUIDE How to Become a Data Scientist

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

What Is Data Science? 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.

Analyzing data and transforming it into useful business guidelines

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.

What Are the Required Skills for Data Science Careers? 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.

How Much Do Data Scientists Make? 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.

City Average 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.

Projected Job Growth Outlook (2018-28): 16%

Number of People Employed: 140,000

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

Position Salary

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 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.

How Can You Become a Data Scientist? 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.

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.

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.

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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