How to get a job in data science

Getting a job in data science can be an undertaking at first, but with a bit of preparation, you can either start a new career in data science or get back into it.

Since data science is an in-demand career with high growth, you’ll likely get a job quickly if you have the skills necessary to complete data-specific tasks. Let’s look at how you fit into this diverse, ever-changing industry.

What is a data scientist?

Data scientists collect and clean substantial amounts of data, interpret data to solve business problems, maintain databases and dashboards, build algorithms, run experiments, and present data to stakeholders using a visual representation of the data.


Why should you pursue a career in data science?

A data scientist has a high salary, a stable job market, and an exciting work environment. Data scientists solve problems for companies to help them reach financial success. Plus, becoming a data scientist is easier than pursuing a career in machine learning or software engineering. You will need to learn how to code to build predictive models, but you don’t need a degree.

What type of data scientist are you?

Data scientists come in many shapes, so you’ll need to understand what fields are in-demand and which positions are more likely to contain your skill-set. Traditional avenues typically include machine learning scientists, statisticians, and actuarial scientists. However, less IT-focused jobs, like quality analysts and business analytic practitioners, also need a high influx of staff.

B2B consulting companies, such as the data science specialists at, speak to businesses about the benefits a data scientist can bring to companies. They offer up their staff to gather and analyze data, so companies can save money on hiring. The options are endless in data science.

Five steps to get a data science job without experience

Got no experience but want a job in data science? Here are five steps you can take.

Step 1: Brush up on your math skills

If you already have a career in an IT, computer science, or engineering field, the transition to data science will be easier, but you should still brush up on the basics to write efficient code.

  • Statistical methods
  • Probability theory
  • Probability distributions
  • Linear algebra
  • Multivariable calculus
  • Hypothesis testing
  • Data summaries and descriptive statistics
  • Statistical modeling and fitting
  • Regression analysis
  • Markov chains
  • Bayesian thinking and modeling

Once you have the foundations of data analysis down, you can start to learn how to code.

Step 2: Learn how to code

The coding language you want to learn depends on the data science job you want to land, but almost all data scientists know SAS, Python, R, and SQL as they’re required for most projects.

  1. SAS: A tool used for statistical analysis, predictive analytics, business intelligence.
  2. SQL: Relationship management tool that joins or questions data across databases.
  3. R: A programming language that can solve complicated stats and math calculations.
  4. Python: A scripting language necessary in software and web development.

Practice these languages daily to get the skills to land your first internship or project.

Step 3: Gain experience with internships and projects

Start skimming freelancing platforms like Fiverr and Upwork to gain experience in your field. Companies will want to see a portfolio full of professional work, and they want to know you can solve basic coding problems. Gaining experience without experience is the trickiest part, but you can ace your interviews if you leverage your community and newfound connections.

Step 4: Become a data analyst

A data analyst and a data scientist aren’t the same things, but they both identify data trends and manage data collection. Getting a job in this field without experience is much easier, and becoming a data analyst first can kickstart your career. Continue to harness your skills.

Step 5: Keep working hard

While working for a company as an intern or data analyst, start speaking to your coworkers and networking. You’ll begin to learn a lot about the industry you’re in, whether or not job growth is possible, and if mentorship or training is available in your company. Referrals are the number one way you’ll get a job as a data scientist starting out, so work on making a good impression.

Photo by Scott Graham