Data scientists gather, analyze, and interpret large data sets from company databases. They use their results to create data-driven solutions to business challenges. Also, they use the results to optimize and improve product development, marketing techniques, and business strategies. Likewise, they use predictive modeling to increase and improve customer experiences, revenue generation, ad targeting, and other business outcomes. Other duties include developing predictive models and machine-learning algorithms, using data visualization techniques to present results, and working with the engineering and product development teams.
To become a data scientist, you need at least a bachelor's degree in statistics, computer science, or a relevant field. Skills like problem-solving, communication, analytical, presentation, and math skills aid success in this role. You must be experienced using statistical computer languages like R, Python, SLQ, and so on. The data scientist can earn as low as $82,000 and a high of $165,000. Their average annual salary is $115,874.
What is a Data Scientist?
What Does a Data Scientist Do
There are certain skills that many data scientists have in order to accomplish their responsibilities. By taking a look through resumes, we were able to narrow down the most common skills for a person in this position. We discovered that a lot of resumes listed logical thinking, math skills and detail oriented.
How To Become a Data Scientist
If you're interested in becoming a data scientist, one of the first things to consider is how much education you need. We've determined that 50.7% of data scientists have a bachelor's degree. In terms of higher education levels, we found that 34.1% of data scientists have master's degrees. Even though most data scientists have a college degree, it's impossible to become one with only a high school degree or GED.
Data Scientist Career Paths
In addition to switching up your job search, it might prove helpful to look at a career path for your specific job. Now, what's a career path you ask? Well, it's practically a map that shows how you might advance from one job title to another. Our career paths are especially detailed with salary changes. So, for example, if you started out with the role of senior software engineer you might progress to a role such as team leader eventually. Later on in your career, you could end up with the title project leader.
Average Salary for a Data Scientist
What Am I Worth?
States With The Most Data Scientist Jobs
Mouse over a state to see the number of active data scientist jobs in each state. The darker areas on the map show where data scientists earn the highest salaries across all 50 states.
Number Of Data Scientist Jobs By State
Top Colleges for Data Scientists
1. Columbia University in the City of New York
New York, NY • Private
2. Carnegie Mellon University
Pittsburgh, PA • Private
3. Harvard University
Cambridge, MA • Private
4. Duke University
Durham, NC • Private
5. University of Pennsylvania
Philadelphia, PA • Private
6. Worcester Polytechnic Institute
Worcester, MA • Private
7. New York University
New York, NY • Private
8. Boston University
Boston, MA • Private
9. Georgia Institute of Technology
Atlanta, GA • Private
10. Cornell University
Ithaca, NY • Private
Top Skills For a Data Scientist
The skills section on your resume can be almost as important as the experience section, so you want it to be an accurate portrayal of what you can do. Luckily, we've found all of the skills you'll need so even if you don't have these skills yet, you know what you need to work on. Out of all the resumes we looked through, 13.5% of data scientists listed python on their resume, but soft skills such as logical thinking and math skills are important as well.
Choose From 10+ Customizable Data Scientist Resume templates
Zippia allows you to choose from different easy-to-use Data Scientist templates, and provides you with expert advice. Using the templates, you can rest assured that the structure and format of your Data Scientist resume is top notch. Choose a template with the colors, fonts & text sizes that are appropriate for your industry.
Data Scientist Demographics
Data Scientist Gender Distribution
After extensive research and analysis, Zippia's data science team found that:
- Among data scientists, 20.4% of them are women, while 79.6% are men.
- The most common race/ethnicity among data scientists is White, which makes up 66.1% of all data scientists.
- The most common foreign language among data scientists is Spanish at 21.3%.
Work Experience Programs For Data Scientists
Virtual work experience programs replicate work at top companies and help you gain the skills to be successful when applying and working there. In only a few hours, learn the relevant tools necessary to complete a typical work day at that company. Virtual work experience programs are 100% free, open-access, and self-paced. No experience or application is required!
Company: Standard Bank
Cost: Free
Duration: 4-4.5 hours
Company: Walmart India
Cost: Free
Duration: 3.5-4 hours
Company: PwC Switzerland
Cost: Free
Duration: 7-8 hours
Company: Accenture North America
Cost: Free
Duration: 5-6 hours
Company: Tata
Cost: Free
Duration: 3.5-4.5 hours
Company: BCG
Cost: Free
Duration: 5-6 hours
Online Courses For Data Scientist That You May Like
Harness the Power of Machine Learning in R for Data/Text Mining, & Natural Language Processing with Practical Examples...
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning...
A primer on Machine Learning for Data Science. Revealed for everyday people, by the Backyard Data Scientist...
Best States For a Data Scientist
Some places are better than others when it comes to starting a career as a data scientist. The best states for people in this position are California, Washington, New York, and Nevada. Data scientists make the most in California with an average salary of $120,196. Whereas in Washington and New York, they would average $111,669 and $98,821, respectively. While data scientists would only make an average of $96,695 in Nevada, you would still make more there than in the rest of the country. We determined these as the best states based on job availability and pay. By finding the median salary, cost of living, and using the Bureau of Labor Statistics' Location Quotient, we narrowed down our list of states to these four.
1. Washington
$111,669
Avg. Salary
2. New York
$98,821
Avg. Salary
3. Delaware
$92,901
Avg. Salary
How Do Data Scientist Rate Their Jobs?
Top Data Scientist Employers
We've made finding a great employer to work for easy by doing the hard work for you. We looked into employers that employ data scientists and discovered their number of data scientist opportunities and average salary. Through our research, we concluded that Microsoft was the best, especially with an average salary of $138,764. Meta follows up with an average salary of $153,148, and then comes Amazon with an average of $124,816. In addition, we know most people would rather work from home. So instead of having to change careers, we identified the best employers for remote work as a data scientist. The employers include Nokia, Booz Allen Hamilton, and VMware
Most Common Employers For Data Scientist
| Rank | Company | Average Salary | Hourly Rate | Job Openings |
|---|---|---|---|---|
| 1 | Airbnb | $153,510 | $73.80 | 216 |
| 2 | Meta | $153,148 | $73.63 | 1,734 |
| 3 | Apple | $147,478 | $70.90 | 314 |
| 4 | Lyft | $142,400 | $68.46 | 150 |
| 5 | $141,242 | $67.90 | 392 | |
| 6 | Microsoft | $138,764 | $66.71 | 2,717 |
| 7 | $138,076 | $66.38 | 156 | |
| 8 | eBay | $136,406 | $65.58 | 161 |
| 9 | PayPal | $135,916 | $65.34 | 255 |
| 10 | Walmart | $130,532 | $62.76 | 579 |
Data Scientist Videos
Becoming a Data Scientist FAQs
Data Scientist Vs. Software Engineer
A data scientist is a tech professional that uses algorithms and statistics to draw insights from data, while a software engineer is someone who uses programming and engineering skills to design software.
Ml Engineer Vs. Data Scientist
ML engineers typically write low-level code to tweak and optimize default implementations, while a data scientist writes higher-level code and often uses BI tools for data analysis and visualization.
How Many Years Does It Take To Become A Data Scientist?
It takes 4 to 5 years to become a data scientist. However, there are so many different paths to get there, so the time it can take to become a data scientist will vary.
Those who go the university route, for example, can become data scientists in 3 to 4 years, or the time it takes them to earn a bachelor's degree. However, most data scientists, over 75% to be exact, have at least a master's in data science. This takes an additional 1 to 2 years to complete.
Is Data Science A Good Career?
Yes, data science is a good career. Careers in data science offer high-paying salaries in many different industries.
Data science is essential in the modern landscape, meaning data scientists are in extremely high demand across a number of industries. It is one of the fastest-growing and highest-paid jobs in tech.
Is Data Scientist A Good Career?
Yes, data scientist is a good career. Data scientists are paid well, have high job satisfaction, good job growth, and can work in a variety of industries.
Data science is one of the most highly paid jobs in any industry. The average data scientist, for example, makes an average of $116,100 per year.
What Qualifications Do You Need To Be A Data Scientist?
The qualifications for a data scientist include the right combination of educational credentials, programing skills, statistics, and business acumen.
After all, a data scientist is part mathematician, part computer scientist, and part business strategist, and as such, they must have expertise in several different disciplines at once.
Machine Learning Engineer Vs. Data Scientist
A machine learning engineer is someone who writes low-level code, while a data scientist is a person who writes high-level code.
A machine learning engineer is a tech professional that writes low-level code to tweak and optimize default implementations. They are also proficient in high-efficiency programming languages such as C++, Java, and Scala. Machine learning engineers focus on scaling models into production while ensuring adherence to business service level agreements.