Skip to main content
HomeBlogCareer Services

How to break into data science

Looking to break into data science? Find out how to get started on your data science journey and what types of opportunities are available today.
Nov 2021  · 6 min read

The COVID-19 pandemic has accelerated digital transformation across all industries. As such, organizations are generating data more than ever, and the need for data scientists has never been higher. According to the LinkedIn 2020 emerging jobs report, Data Scientist is the number three fastest-growing job on the market (37% annual growth), only trailing other data-intensive jobs such as robotics engineer and artificial intelligence specialist. This growth does not seem to be slowing down, with the US Bureau of Statistics reporting 11.5 million new data science jobs by 2026 alone.

In this blog post, we take a closer look at what data science is, the types of career opportunities in this space, and some best practices for breaking into data science.

What exactly is data science

In a nutshell, data science is an interdisciplinary field combining programming, statistics, artificial intelligence, and business subject matter expertise that seeks to extract meaningful insights from data. Data science is responsible for delivering some of the most valuable and visible applications in our lives. Here are a few of the use-cases that data scientists work on regularly:

  • Recommendation engines: One of the most common data science applications is recommendation engines like which you see in entertainment applications such as Netflix, Spotify, or Youtube.
  • Time-series forecasting: Whether stock prices, sales, or energy consumption forecasting, data scientists regularly work with and forecast time-series data.
  • Supply chain management: Data scientists are reinventing supply chain management by using data to optimize supply and demand planning, improving shipping processes, and more.
  • Dashboards and analytics: Data scientists help decision-makers make better decisions. A key way of doing this is by unearthing never-before-seen insights from data with the use of dashboards.

The different types of data science jobs

Data science is often used as an umbrella term for any form of data-related work. As such, there’s a spectrum of roles within this space that are all equally exciting and important. Here are the most common job titles you can find in data science and what they all mean:

  • Data Scientist: Data Scientists investigate, extract, and report meaningful insights unearthed from an organization’s data. They communicate these insights to non-technical stakeholders and understand machine learning workflows and how to tie them back to business applications. Data scientists use a wide variety of technical skills to perform their roles and leverage tools like Python, R, SQL, and more.
  • Data Analyst: Data Analysts are responsible for analyzing data and reporting insights from their analysis. They have a deep understanding of the data analysis workflow and report their insights through a combination of coding and non-coding tools such as Python, R, SQL, Tableau, or Power BI.
  • Machine Learning Scientist: Machine Learning Scientists are responsible for developing machine learning systems at scale. They derive predictions from data using machine learning models to solve problems like customer churn and customer lifetime value. They are responsible for deploying these models for the organization to use.

Did you know? DataCamp is hiring for various roles, from data scientists, machine learning experts to directors of analytics. If you’re passionate about data science, but feel like your technical skills aren’t fully there, check out other job postings across product, marketing, and content.

How to break into data science

While there is no one-size-fits-all approach to breaking into data science, here are a few pointers that can push you in the right direction.

  • Education: Most data science roles require a bachelor’s degree to break into. More importantly, it’s important to showcase that you have the necessary skills to work with programming languages, statistics, and machine learning. Options range here from traditional education to online learning providers and bootcamps.
  • Showcase a portfolio of projects: One of the best ways to showcase your knowledge and skills is through a portfolio of projects. The best portfolios contain passion-driven work on datasets that genuinely excite you, not on widely known datasets like Titanic or MNIST. Check out DataCamp Workspace’s publications to see different types of portfolio projects.
  • Consider getting certified: Certifications are a great way to supplement your portfolio and prove your skills. DataCamp's data science certification is highly regarded by leading employers and will help you prove your expertise to hiring managers.
  • Get experience: A great way to convince hiring managers of your skills is by proving that you’ve already done the work. You can do this through internships, graduate schemes, temporary job placements, freelance work, and more.
  • Double down on your non-technical skills: Graduates of liberal arts not only bring great soft skills to the table, but they also possess critical thinking and decision-making skills. Degrees in Economics, Psychology, Sociology, or even Journalism, all contribute to being successful in a multidisciplinary such as data science. Moreover, In the age of ethical AI, non-technical skills such as empathy, active listening, and creative thinking are huge assets.

The future of data science

Throughout this article, we’ve seen how data science is becoming more and more integral for organizations and how that’s fueling its growth. This will only intensify even more. There is reason to believe that the demand for the title “data scientist” may decrease over time, but the need for data skills will not, as data culture and upskilling are top of mind for organizations to remain competitive in the data-driven age.

If you want to be part of the data revolution, consider joining DataCamp, or start learning today and join our community of 9 million+ learners.

Data Science Concept Vector Image


How to Become a Data Scientist in 8 Steps

Find out everything you need to know about becoming a data scientist, and find out whether it’s the right career for you!
Jose Jorge Rodriguez Salgado's photo

Jose Jorge Rodriguez Salgado

12 min


Applying for data science jobs and how to set yourself apart

Learn how to apply for the jobs you desire and set your self apart. Learn what makes you stand out and what steps to take stand out from crowd.
DataCamp Team's photo

DataCamp Team

9 min


How to Become a Freelance Data Scientist (pt.1)

Discover the hard and soft skills you'll need as a freelance data scientist, as well as the pros and cons of choosing this independent career path.
Çağlar Uslu's photo

Çağlar Uslu

11 min


How to Switch Into a Data Science Career

Six powerful lessons we wish we’d known before switching into data science six months ago.
Omdena Team's photo

Omdena Team

8 min


7 Top Data Science Careers and How to Pursue Them

Examining the incredibly popular field that is data science
DataCamp Team's photo

DataCamp Team

13 min


Learn Data Science - Infographic

Start your data science journey now and follow these 8 steps to learn data science.
Karlijn Willems's photo

Karlijn Willems

3 min

See MoreSee More