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Entry-Level Data Scientist Salary Who Earns What
Data Science

Entry-Level Data Scientist Salary: Who Earns What?

9 minute read | June 5, 2023
Monica J. White

Written by:
Monica J. White

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Last year, Glassdoor listed the role of data scientist as being the third-best job in America, and it’s easy to see why. Entry-level salaries regularly exceed six figures, and the role offers a median base salary of $120,000 per year.

But while that average is appealing, it’s just that—an average. Data scientist salaries are not standardized, and the pay can vary depending on a number of factors.

In this article, we’ll address everything there is to know about entry-level data science salaries. We’ll look at how role, industry, location, and education affect salaries and go over our top tips for increasing your compensation.

What Is the Average Salary for an Entry-Level Data Scientist?

According to Glassdoor, the median average data scientist salary for entry-level roles is $113,894. This data is based on salary information in the United States and includes additional pay such as benefits and stock shares.

Entry-Level Data Scientist Salaries

The following salary data is split into four categories: salary by role, by industry, by location, and by education. Each of these factors can influence your rate of pay both during your time as a junior data scientist and once you’ve gained seniority.

By Role

Data scientists can have different specialties that affect their job titles and the salaries they receive.

Data Science Intern

data scientist salary entry-level, by role, Data Science Intern

Internships are usually completed during or soon after completing a college degree and can be either paid or unpaid. For a paid data scientist intern, the median average salary is $96,982.

Junior Data Scientist

data scientist salary entry-level, Junior Data Scientist.png

The title of “Junior data scientist” is a popular role for data scientists in their first or second year on the job. It doesn’t denote any specialties, so you can often expect a varied set of responsibilities and opportunities to learn new skills.

Junior Data Engineer

data scientist salary entry-level, Junior Data Engineer

Data engineers and data scientists have similar responsibilities, especially when it comes to data analysis. However, data engineers also focus on developing systems for collecting and storing data.

Junior Machine Learning Engineer

data scientist salary entry-level, Junior Machine Learning Engineer

Machine learning is a part of data science that focuses on predictive modeling and improving the efficiency of dealing with large data sets. Because it’s a specialized field that requires specific education and skills, it often pays more than general data scientist roles.

By Industry

Data scientists are valued differently from industry to industry, so it’s important to pay attention to the average base salaries in each industry.

Banking, Finance, and Insurance

data scientist salary entry-level, by industry, Banking, Finance, and Insurance

Data scientists working in banking and finance are often akin to financial advisors, as they take existing data and make predictions about future prospects. It’s one of the most lucrative industries a data scientist can work in.

Healthcare and Pharma

data scientist salary entry-level, Healthcare

Data scientists are also needed in the healthcare industry to help make predictions about certain diseases and the efficacy of medications.

Technology

data scientist salary entry-level, Technology

Data scientists working in tech can have a range of roles and responsibilities, but the through-line is that tech companies tend to generate a lot of data, which data scientists can analyze to help inform business decisions.

Retail and E-Commerce

data scientist salary entry-level, Retail and E-Commerce

The canny ability of online retailers to make product recommendations is largely due to the work of data scientists. But that’s just one way in which retail and e-commerce use data scientists. They also help predict when will be the most lucrative time to do sales, and how to best price products.

Tourism

data scientist salary entry-level, Tourism

Airlines and similar travel providers need data scientists to help them predict demand, and price their services accordingly.

Agriculture

data scientist salary entry-level, Agriculture

Agriculture has always been an unpredictable industry, but data scientists are helping to change that by analyzing the wide range of factors that can impact crops.

Media

data scientist salary entry-level, Media

Data scientists help media conglomerates tailor suggestions to their viewers and also help executives determine what kinds of content viewers want to see.

Transportation and Logistics

data scientist salary entry-level, Transportation and Logistics

Shipping and logistics companies are constantly trying to figure out how to best allocate their resources to get things where they need to go in the shortest amount of time. Data scientists are key to making this happen.

Manufacturing

data scientist salary entry-level, Manufacturing

Manufacturing is a complex process that entails looking at a variety of data points and data sets, making this industry ripe for the kind of work done by data scientists.

By Location

Location can have a big impact on salaries in any industry or career, and data science is no exception. Here we’ll compare salaries in countries around the world with the salaries in the United States. While each salary will be converted to U.S. dollars, bear in mind that direct comparison isn’t always very useful due to the stark differences in the cost of living.

USA

data scientist salary entry-level, by location, US

For data scientists in their first year of work, the national average salary in the United States is $113,792.

UK

data scientist salary entry-level, UK

The average salary in the United Kingdom converts to around $59,522.

India

data scientist salary entry-level, India

The average salary in India converts to around $11,624 a year.

Australia

data scientist salary entry-level, Australia

The average salary for junior data scientists in Australia equates to $71,958.

Germany

data scientist salary entry-level, Germany

The average data science salary in Germany converts to $66,841.

South Africa

data scientist salary entry-level, South Africa

In South Africa, the average salary for entry-level data scientists converts to around $23,428.

Norway

data scientist salary entry-level, Norway

Salary Range: NOK 642,000-NOK 721,000

Median Salary: NOK 671,175

In Norway, the average salary is around $62,866 when converted to U.S. dollars.

By Education

Education can also have some impact on your salary, but typically less so than location and industry. Current research shows that 76.6% of data scientists hold a master’s or PhD degree and 19.8% have a bachelor’s degree.

However, it also shows that the number of individuals whose first job title was “data scientist” is also on the rise (22.6%), showing that the field is beginning to expand beyond senior tech workers who transition into data science after gaining 5-8 years of experience elsewhere. 

No Degree

If you break into data science without a degree, you will likely still be applying to roles that list at least a bachelor’s degree as a requirement. This means your average salary would be no less than what a data scientist with a bachelor’s degree gets paid.

Bachelor’s Degree

data scientist salary entry-level, by education
Source: Glassdoor

For new data scientists with a bachelor’s degree, the average salary range is $88,151-$93,553. It’s common to see postings like this one, which ask that candidates at least have a bachelor’s degree. However, data science bootcamps are quickly becoming the norm, and are replacing this requirement. 

Master’s Degree

If you enter data science with a master’s degree, you may be able to start on a higher salary, but it’s not a guarantee. The average range is similar to those for bachelor’s degree holders at $85,000-$105,000.

How To Boost Your Data Scientist Salary

While the data we’ve presented here can help you choose the best-paying option for your first data science job, boosting your salary is all about what you do after you land your first role.

  1. Follow the Work (and the Money)

  2. Expand Your Skill Set

  3. Negotiate the Job Offer

  4. Get More Experience

  5. Specialize

  6. Ask for a Salary Review

  7. Don’t Be Afraid To Switch Jobs

Follow the Work (and the Money)

Location is a big factor in what work you can get and how much it pays. Whether you’re a fresh graduate entering the workforce or switching careers later on in life, being open to relocation is very likely to help your career and your salary. Metropolitan areas in the United States, for example, usually have substantially higher pay rates for data scientists compared to other places.

Expand Your Skill Set

Building up work experience is a large part of earning promotions and new positions, but it’s also important to put direct effort into expanding your skills. You can do this during work to some extent, but if you want to develop technical skills in a different area, you will need to study outside of work as well. Adding to your skill set will help you reach higher pay bands in your current area, or help you transition into better-paid areas.

Negotiate the Job Offer

Assess the value you’ll bring to that team or department, how important your projects are, and who else has enough domain knowledge to take them on. All of these things will help you gauge the right pay band or salary. If you fill a critical gap, then you can use this to leverage a higher salary.

Get More Experience

Working on personal data science projects or getting involved in other projects at your company is a great way to expand and gather more hands-on experience. The extra things you work on are also effective talking points during interviews that showcase your passion and drive for your data science career.

Specialize

Specializing in the specific field you enjoy or excel in is a great way to increase your value as an employee and command a higher salary. With an attention to detail and a commitment to quality, you can easily find ways to push your work and engage in personal projects that will develop your skills. You can also get certified in various fields to showcase your specialization.

Ask for a Salary Review

Asking for a salary review can do two things: raise your salary, or show your manager that you’re serious about climbing the ladder. While only one provides instant success, both outcomes can be good for your career. In other words, there’s no downside to trying. If you believe your contributions are worth slightly more than you receive, put together your thoughts and reasoning and ask for a salary review.

Don’t Be Afraid To Switch Jobs

Changing employers can feel daunting because it’s impossible to know for sure if you’re moving into a better position. However, keeping an eye out on current openings can help you spot higher-paying roles. You can apply based on the salary, find out more during the application process, and by the time you need to make a decision, you’ll have the information you need.

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Becoming a Data Scientist: Quick Career Overview

Before you start your data science journey, it’s useful to know exactly what data scientists do and what their qualifications are.

What Does an Entry-Level Data Scientist Do?

Entry-level data scientists will often be part of a team of more senior members. At first, your assignments will likely be low-level tasks involving mining and cleaning data, or debugging systems that are showing problems.

The main objective of a data scientist is to use data-driven insights to answer important questions posed by the stakeholders of the company. The methods of doing so won’t be obvious, so data scientists need to be creative in what kind of data they use and how they use it.

General Requirements To Become a Data Scientist

FAQs About the Role

We’ve got the answers to your most frequently asked questions:

Is Being a Data Scientist Stressful?

Data science isn’t objectively stressful, but job satisfaction and stress levels depend a lot on how passionate you are about the job. Glassdoor reports a 4.1 out of 5 job satisfaction rating for data scientists, ranking the third-best job in the U.S. for compensation, satisfaction, and job openings.

How Do You Know if Data Science Is for You?

If you’re interested in data science, but you don’t know enough yet to make any big decisions, you can try out introductory prep courses online. These take you through the basics and help you see what kind of skills you need and what kind of problems data scientists face. You’ll also get beginner-level lessons in Python, so you don’t need to have prior experience in programming.

How Long Does It Take for a Newcomer To Become a Data Scientist?

You can learn enough foundational knowledge to start applying to entry-level data science roles in six months to a year.

Can You Become a Self-Taught Data Scientist?

Self-studying data science from scratch is possible with online resources, but it can be useful to take your study one step further by enrolling in a data science bootcamp.

What Does the Career Path of a Data Scientist Look Like?

Many current data scientists transitioned into the field after spending 5-10 years in a related tech field. However, this is largely due to how the field emerged and gained popularity. Recently, more and more people are starting their professional careers in data science, and moving into senior or specialized roles as their career progresses.

Since you’re here…Are you interested in this career track? Investigate with our free guide to what a data professional actually does. When you’re ready to build a CV that will make hiring managers melt, join our Data Science Bootcamp which will help you land a job or your tuition back!

About Monica J. White

Monica is a journalist with a lifelong interest in technology, from PC hardware to software and programming. She first started writing over ten years ago and has made a career out of it. Now, her focus is centered around technology and explaining complex concepts to a broader audience.