How to Become a Data Scientist

Author: Staff

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Companies of all kinds are working to collect and understand the ever-increasing volumes of data at their fingertips. The nuggets hidden within raw facts and figures hold the answers to important and impactful business questions—as long as you know how to find and apply them. That’s exactly what data scientists do, along with a host of other responsibilities that help businesses and organizations make better decisions. If you’re wondering how to become a data scientist, we’ll share information about what data scientists do, their typical salary, and the path to becoming a data scientist.

 

What Is a Data Scientist?

Data scientists analyze and interpret the disparate data coming into organizations in many different formats from multiple sources. These experts are today’s problem-solvers and discovery-makers, helping businesses and organizations capitalize on big data by extracting valuable insights from it.

What else is a data scientist? A communicator and advisor. Data scientists know how to visually present information in clear, compelling ways. As they make new discoveries, data scientists can effectively communicate what they’ve learned, explain the implications of their findings, and help generate ideas and build new solutions as a result.

 

What Does a Data Scientist Do?

So, what does a data scientist do? And how do they make an impact on an organization?

Many industries now rely on data science to make strategic decisions and improve business outcomes. Here are a few real-world examples of what a data scientist can do.

What Does a Data Scientist Do in Health Care?

Data science is especially important in the health care environment, as it can improve health care delivery and telehealth, as well as give providers critical insights about their patients. A data scientist in the health field may examine medical records, surveys, lab results, and clinical trials information to make accurate projections about disease prevention and progression.

They may analyze prescriptions to prevent drug abuse. Or, they may work with other data scientists to improve the patient experience of a health care delivery application.

What Does a Data Scientist Do in Manufacturing?

In manufacturing settings, data scientists might use information from warehouse management systems to accurately forecast the demand for a specific product. They may also predict periods of increased need and determine how to best allocate resources to handle these surges. Rather than relying on instinct, a data scientist provides the data-driven analysis necessary to make better hiring, purchasing, and operational decisions.

What Does a Data Scientist Do in a Retail Environment?

Here, data scientists might analyze the sales results of recent promotions and campaigns to determine what prompts a consumer to buy products. This information can help companies pinpoint what types of customers are most likely to take advantage of future events. Data scientists in the retail sector may also offer insight that helps retailers make better decisions about how to price their products, what types of deals to offer, and when to offer them.

In a Nutshell…

Almost every type of organization can use data to its advantage if it has a data scientist at the helm to help find, analyze, and apply the right information to make better decisions, improve performance, and meet goals faster.

 

How to Become a Data Scientist: 11 Steps

There’s no specific path to follow to become a data scientist, but there are certain steps you can take to build a competitive advantage in the field. Here are several steps you can take to help you become a data scientist:

  1. Earn a bachelor’s degree in data science or a related field. Information technology, computer science, math, or management information systems can all help you in your journey to become a data scientist. While these degrees aren’t always required to become a data scientist or get accepted into a master’s in data science program, they help you get your footing in the field, especially if you want to get a master’s degree later.
  2. Take any opportunity to use data science skills. Whether you’re working in a data science role or not, volunteering for special projects that require data science proficiency can help you exercise data science skills. Even if you feel like you don’t have much to contribute, you can learn a lot just from being involved. There are many opportunities to voluntarily contribute data science skills to community projects focused on everything from forecasting water and energy demand to modeling earthquake damage. The more hands-on experience you can get, the better.
  3. Research master’s programs in data science. Many employers are looking for professionals with advanced degrees, and the field of data science is no exception. A master’s degree in data science serves as your ticket to senior-level positions, higher salaries, and leadership and management opportunities. An online program even lets you continue working while you earn your degree.
  4. Consider an executive certificate program. If you’re not ready for a master’s degree, an executive certificate can serve as an introduction to data science, helping you build a practical understanding of the basics, including machine learning and big data.
  5. Attend online info sessions to learn more about the data science program(s) you’re considering so you can hear from faculty, alumni, and current students. You’ll learn how the program can fit into your life, discover more about the curriculum, and get tips on applying
  6. Choose a reputable master’s in data science program. Earning your Master’s in Data Science from an institution known for excellence and innovation will set you apart as a candidate in a growing field. The right program prepares you to use powerful tools to analyze data, unpack the stories big data can tell, and ethically approach data analysis.
  7. Build core competencies that will prepare you for a data science career: predictive analytics, statistical modeling, databases and, data security, and data visualization.
  8. Sharpen your communication skills. An important part of becoming a data scientist involves being able to convey your thoughts and findings in an impactful way. Practice your presentation skills to help you become comfortable presenting in front of larger groups.
  9. Build your network as you go. Get to know and interact with the faculty, students, and alumni who make up the graduate experience. Building this community can connect you with industry leaders and new career opportunities. Some graduate programs in data science focus on cultivating a tight-knit learning community of students and alumni, so look for programs that already have this community built-in.
  10. Build a portfolio that showcases your work. Include algorithms built from the ground up, meaningful analyses, presentations that capture your insights, and other work you’ve completed.
  11. Always watch for career opportunities that seem like a good fit. An impressive master’s degree in data science from a reputable institution, along with a meaningful portfolio and robust network, will quickly help you advance your career.

 

A Typical Data Scientist Job Description

Now that you understand how to become a data scientist, it’s also important to know what employers will be looking for as they fill these key positions.

It takes a unique combination of technical and soft skills to bring different worlds of data together and make life-changing impacts. These skills will be at the top of the list when you become a data scientist:

  • Collecting, inspecting, cleaning, and transforming data
  • Building dashboards and reports
  • Working with computer languages like Java, R, Python, and SQL
  • Deploying machine learning to automate model building
  • Identifying patterns and drawing conclusions based on data
  • Creating graphical representations of information
  • Communicating findings and recommendations to key stakeholders

Although you may not see soft skills outlined as clearly in a job description, data scientists will also be expected to:

  • Conduct analytical and critical thinking, with the ability to ask probing questions and reflect on the information you have
  • Look beyond the surface to discover patterns and solutions
  • Possess excellent interpersonal skills to communicate with diverse audiences across all technical levels
  • Work freely, experimenting and exploring new possibilities

 

Salary and Career Outlook for Data Scientists

What is a typical data scientist's salary, and what’s the job market like?

Glassdoor ranks data scientists as No. 3 on its list of 50 Best Jobs in America for 2022 (followed by data engineers at No. 7)—and it’s been at the top for a few years in a row. This ranking is based on the number of job openings across the country, job satisfaction levels, and median base salary.

Within the field, the chance of career advancement is high. Because organizations of all kinds are producing data that needs to be put to better use to maximize time, resources, costs, and labor, demand is strong. As data scientists gain experience and earn advanced degrees—such as a Master’s in Data Science—they often move into senior-level positions with even higher pay.

The U.S. Bureau of Labor Statistics also forecasts strong data science career growth, with the number of jobs rising by nearly 28% (11.5 million jobs) through 2026.

Career opportunities tend to be even more impressive for ethical, three-dimensional professionals who have advanced degrees and strong statistical, technical, and communication skills. All students in Notre Dame’s last data science cohort were employed within six months of graduation, securing promotions or new positions.

 

Gain a Competitive Edge With Notre Dame’s Online Master’s in Data Science

 

Notre Dame’s Online Master’s in Data Science program creates three-dimensional leaders who have quantitative and computational data skills along with the ability to communicate effectively and act ethically. This unique combination gives you the edge you need to perform at the highest levels in the field.

Our Master’s in Data Science program was designed to provide students with the technical skills, quantitative aptitude, and analytical insight that the industry now demands. Take six credits per semester for five consecutive semesters to earn your degree—with no worries about navigating complex electives models.

Whether you just earned your undergraduate degree, have a few years of work experience, or are an experienced data science professional, the Master’s in Data Science program at the University of Notre Dame gives you the flexibility and convenience of an online program plus connection and support through in-person immersions and personal interaction.

You’ll get to learn in a community of current and future leaders and ethical innovators. To make sure you’re prepared for what’s ahead, our curriculum constantly shifts to cover new evolutions and advances.

If you’re not ready for a full master’s degree, the executive certificate program in data science is also available. This program offers an overview of data science concepts, machine learning, and big data. Apply today to get on the path to becoming a data scientist—and experiencing the Notre Dame Edge.

 

“I absolutely love the [data science] program. I have never lost interest in what we’re learning or felt things were too difficult. It is challenging, but I have resources to get through it. The online material is so good, and I’ve never had a single instructor who came to class without preparation.”

Sunela Thomas, Class of 2021, Director of Compliance