Data scientists are analytical experts who extract meaning from and interpret data to solve complex problems. They use industry knowledge, contextual understanding, and skepticism of existing assumptions to uncover solutions to business challenges.

A data scientist’s role combines computer science, statistics, and mathematics to collect and organize data from many different data sources, translate results into actionable plans, and communicate their findings to their organizations. Successful data scientists must be effective communicators, leaders, team members, and high-level analytical thinkers.

Data scientists work in various industries, including tech startups, government agencies, healthcare, manufacturing, and research institutions. Data scientists are highly sought after in today’s data and tech-heavy economy, and their salaries and job growth reflect that.

Here are six common steps to consider if you’re interested in pursuing a career in data science:

Step 1. Pursue an undergraduate degree in data science or a closely related field

Step 2. Consider a specialization

Step 3. Get your first entry-level job as a data scientist

Step 4. Advance your skills with a data science bootcamp

Step 5. Review additional data scientist certifications and post-graduate learning

Step 6. Earn a master’s degree in data science

You will generally need at least a bachelor’s degree in data science or a computer-related field to get your foot in the door as an entry-level data scientist. However, some data science careers require a master’s or doctoral degree. Degrees add structure, internships, networking, and recognized academic qualifications to your résumé. However, if you’ve received a bachelor’s degree in a different field, you may need to focus on developing skills required for the job through continued education, like online short courses or bootcamps.

Data scientists may specialize in a particular industry or develop strong skills in areas such as artificial intelligence, machine learning, research, or database management. Specialization is a good way to increase your earning potential and do work that is meaningful to you. 

Once you’ve acquired the right skills and specialization, you should be ready for your first data science role! Creating an online portfolio is a valuable tool to display a few projects and showcase your accomplishments to potential employers. You also may want to consider a company with room for growth since your first data science job may not have the title data scientist but could be more of an analytical role. You’ll quickly learn how to work on a team and best practices that will prepare you for more senior positions.

Data science bootcamps are short-term, immersive educational programs that teach critical data science skills and programming languages such as Python, R, and SQL. Many bootcamps are online; some may take a couple of weeks to complete, while others may take up to a couple of months. Bootcamps may help you expand your network and can offer dedicated career services to help with job placements after graduation. Data science bootcamps typically cover various topics such as machine learning, natural language processing, data analytics, data visualization, and more.

Here are a few certifications that focus on valuable skills:

Certified Analytics Professional (CAP)

SAS Certified Predictive Modeler using SAS Enterprise Miner 14

Academic qualifications may be more important than you imagine. When it comes to most data science jobs, is a master’s required? It depends on the job; some working data scientists have a bachelor’s or graduated from a data science bootcamp. According to a 2022 Burtch Works study, over 90% of data scientists they surveyed hold a graduate degree. 

Learn about 23 schools with master’s in data science programs.

The day-to-day responsibilities of a data scientist can vary. Some of the different tasks that data scientists are responsible for can include the following:

Every company will have a different take on a data scientist job description. Some treat their data scientists as data analysts or combine their duties with data engineers; others need top-level analytics experts skilled in intense machine learning and data visualizations.

As data scientists achieve new levels of experience or change jobs, their responsibilities invariably change. For example, a person working alone in a mid-size company may spend a good portion of the day in data cleaning and munging. A high-level employee in a business that offers data-based services may be asked to structure big data projects or create new products.

Data scientists don’t need just to understand programming languages, management of databases, and how to transpose data into visualizations – they should be naturally curious about their surrounding world through an analytical lens. Possessing personality traits that resemble quality assurance departments, data scientists may be meticulous as they review large amounts of data and seek out patterns and answers. They are also creative in making new algorithms to crawl data or devising organized database warehouses.

Generally, professionals in the data science field must know how to communicate in several different modes, i.e., to their team, stakeholders and clients. There may be a lot of dead ends, wrong turns, or bumpy roads, but data scientists should possess drive and grit to stay afloat with patience in their research.

According to the Bureau of Labor and Statistics (BLS), the employment growth of computer information and research scientists, which include data scientists, from 2021 to 2031 is 21%. The demand for experienced data scientists is high, but you must start somewhere. Some data scientists get their foot in the door working as entry-level data analysts, extracting structured data from MySQL databases or CRM systems, developing basic visualizations in Tableau, or analyzing A/B test results. If you’d like to push beyond your analytical role – think about what you could do with a career in data science:

Companies of every size and industry – from Google, LinkedIn, and Amazon to the humble retail store – seek experts to help them wrestle big data into submission. In certain companies, “new look” data scientists may find themselves responsible for financial planning, ROI assessment, budgets, and a host of other duties related to the management of an organization.

A data scientist’s salary depends on years of experience, skillset, education, and location. According to The Burtch Works Study, employers place greater value on data scientists with specialized skills, such as Natural Language Processing or Artificial Intelligence. The BLS claims skilled computer research and information scientists, which include data scientists, enjoy excellent job prospects because of high demand. Salary data below comes from 2021 data from the Bureau of Labor Statistics.

Data Scientist

Average Data Scientist Salary: $131,490 per year

Lowest 10%: $74,210

Highest 10%: $208,000

Tech bootcamps are a quick way to gain experience with data science and become knowledgeable in programming languages such as Python, R, and SQL. Data science bootcamps are short programs offered in various formats, including part-time, full-time, online, or on-campus. Some bootcamps may take a couple of weeks to complete, while others may take up to a couple of months. Bootcamps may help you expand your network and can offer dedicated career services to help with job placements after graduation.

During the bootcamp, you’ll work on projects and create a portfolio to demonstrate your abilities to potential employers. Data science bootcamps typically cover various topics such as machine learning, natural language processing, different types of data analytics, data visualization, and more. Some related bootcamp programs are:

When researching bootcamps, it is important to consider your career goals and what you’d like to get out of the program. Some bootcamps are geared toward beginners, while others are better suited for those with some programming or computer science experience. You may also want to consider the background of the instructors teaching the bootcamp and the cost. Can you take time off and commit to a full-time immersive experience? Does the bootcamp offer scholarships or discounts? Make sure to ask about all of your financing options.