Data points on colourful background with the words Data Science: Careers, Salaries and Skills

It’s been said that you can’t improve what you don’t measure. Data gives businesses the information they need to make informed decisions—and they’ll pay good money for this type of information.

If you’re good with numbers, have a healthy sense of curiosity, or simply have an interest in data science, this article is for you. We’ve put together all the information you need to make an informed decision about pursuing a career in data science.

We’ll cover the breakdown of different data science positions, what skills are needed, and expected salaries.

Let’s begin.

What Is Data Science?

Data science is an interdisciplinary field of work and study that uses scientific methods, processes, algorithms, and systems to gather information from data and turn it into actionable insights. The data extracted can analyze the past or make predictions about the future. How data is used depends primarily on the data science job and the title of the person working with it.

What Is the Difference Between Data Science and Web Development?

Data science and web development are two very different concepts. Although they both require similar skill sets and both involve computer work, it’s important to understand the difference:

Data science is the collection, cleaning, and analyzing of data from various sources to build reports, dashboards, algorithms, models, and machine-learning tools. In contrast, web development is the process of creating websites or web applications.

Get a head-to-head comparison in this detailed breakdown of Data Sci vs Web Dev >>

What Type of Careers Can You Get in Data Science?

Data science careers include common job titles such as:

  • Data analyst
  • Senior data analyst
  • Junior data analyst
  • Data scientist
  • Senior data scientist
  • Data systems developer
  • Machine learning engineer
  • Data mining engineer
  • Business intelligence developer
  • Data systems analyst

Many data science positions begin as junior, with the opportunity to grow into more senior roles. While advanced data positions require more extensive experience, skills, and tenure, Lighthouse Labs Data Science Bootcamp sets graduates up to secure amazing entry-level positions and start their careers in data. All paths to data science look different—it’s not a vocation reserved exclusively for people with a background in STEM. Even if your resume isn’t what a typical profile looks like, we can help you prepare to take the leap into this exciting career!

Data science careers

For this article, we’ll be speaking in-depth about the following data science career opportunities, as these are the most popular and good jumping-off points into more specialized careers:

  1. Data Analysts
  2. Data Scientists
  3. Machine Learning Specialists

1. Data Analysts

Data science can lead you into a career as a data analyst. Data analysts examine and interpret data sets to draw insights about things that have happened and to present coherent stories through visualizations. Data analysts implement basic scripts and report generation pipeline code but typically are not expected to develop software.

Skills needed to become a data analyst

Skills needed to succeed as a data analyst include analytical skills, technical skills, and communication skills. You will need to have proficient problem-solving skills to effectively analyze data and strong technical skills to build data dashboards that are easy for non-technical individuals to understand. Technical skills include statistical and scripting languages such as R and Python as well as the use of analytics tools such as Tableau, Periscope, and Excel. Communication skills are necessary to help you understand context and present information clearly. Baseline skills in mathematics and statistics are a bonus.

The best thing about pursuing a career in data science is that all of the necessary skills can be learned through the right data science bootcamps or courses. Lighthouse Labs has been helping students bridge the skills gap and enter the data science industry with confidence.

Find out how your skills and experience stack up to data industry expectations Take the Skills Gap Quiz

How to become a data analyst

To become a data analyst, it’s beneficial to have post-secondary education in mathematics, economics, physics, or computer science. This can be in the form of a bachelor’s degree, Master's, or Ph.D.

However, not all employers will require post-secondary education to become a data analyst. Most employers will ask for some sort of formal education in analytics, statistics, computer science, mathematics, or engineering, which can be done through online education platforms such as Lighthouse Labs.

Start building your data analytics skills with Lighthouse Lab’s 6-week Intro to Data Analytics course.

2. Data Scientists

Data science can lead you into a career as a data scientist where you use raw data, statistics, and deep learning to create predictions and analyze opportunities through tools and software you develop. Data scientists create guiding insights for businesses based on industry trends and patterns. Workflows can include reporting and data pipelines, as well as machine learning, project management, and software development workflows.

Skills needed to become a data scientist

Skills that benefit aspiring data scientists include probability, statistics, calculus, algebra, programming, database management, machine learning, deep learning, and data visualization. Data scientists work with business intelligence tools and must be able to code and develop parts of a tool, feature, or software product when necessary.

Every skill that is required to become a successful data scientist can be learned through an accredited program such as a data science bootcamp with Lighthouse Labs. You don’t need any previous experience to excel in the program. Lighthouse has been helping students bridge the technical gaps to reach their dream careers as data scientists.

How to become a data scientist

To become a data scientist, it’s helpful to have an understanding of common programming languages before obtaining a bachelor’s degree in statistics, computer science, information technology, math, or even data science if it’s available.

If you’d like to fast-track your career as a data scientist, you may also choose to pursue specialized training through online programs, such as Lighthouse Labs Data Science Bootcamp.

Once you have the necessary education, you’re able to enter the workforce in an entry-level position (usually as a junior data scientist) where you’ll learn additional skills such as data management programs, database systems, cloud platforms, and more.

As you work your way up to more senior positions, you may want to consider pursuing your master's degree or Ph.D. to further your education in data science, computer science, information technology, math, or statistics. The more education you have, the more sought after you’ll be.

Should you pursue data analysis or data science?

3. Machine Learning Specialists

Another career that data science can lead you to is as a machine learning specialist—otherwise known as a machine learning engineer. Machine learning engineers develop AI algorithms and devices using programming languages such as Python, Java, and Scala to run experiments with the appropriate machine learning libraries. Machine learning is a branch of AI that focuses on data and algorithms to enable machines to learn a task with minimal human intervention.

Skills needed to become a machine learning engineer

To become a machine learning engineer, you must be skilled in programming, probability and statistics, data modelling, machine learning algorithms, and system design.

Get some initial machine learning engineer skills with our free Python crash course. Enroll for Free

How to become a machine learning engineer

To become a machine learning engineer it’s advantageous to complete an undergraduate degree in math, data science, computer science, computer programming, statistics, or physics.

You typically can’t jump into a career as a machine learning engineer without any experience so experience as a software engineer, software programmer, software developer, data scientist, or computer scientist are typical pathways. The majority of machine learning engineer jobs require more education than an undergraduate degree so plan to receive a master’s degree in data science, computer science, software engineering, or even a PhD in machine learning.

Learn more about the career path of a Machine Learning Specialist >>

Data Science Work Opportunities

While data science is still a relatively new career field, there are opportunities in nearly every professional space upon graduation including tech startups, government agencies, large companies, and research institutions. Learning the basic foundations of data science opens many doors for aspiring data specialists to create a successful, versatile, exciting, and rewarding career.

Is Data Science Really in Demand?

Data science is absolutely in demand as businesses need to deliver a five-star online experience to their customers in order to compete in their respective markets. As technology advances and more people are looking online for solutions to their problems (especially in a post-pandemic world), businesses are doing their best to keep up with growing demands.

Data science is needed to help businesses analyze their efforts and steer their decisions for what is to come in the future. With the direction of the world and its reliance on technology, there is no doubt that data science will continue to grow in demand and offer promising careers to those who are early adopters.

Is Data Science a Good Career Option?

Data science is a good career option because of the many perks that make it a desirable role. Some of the perks include competitive salaries, health benefits, work from home and flexible hour opportunities, a healthy mix between technical and interpersonal, and the tremendous amount of opportunity available for advancement into more senior roles. A career in data science can offer a lifetime of professional growth because of the movement opportunities “up” the ladder as well as laterally among the field. Data science jobs also guarantee continued education opportunities which can serve as leverage for salary increases.

Learn how an education in data science translates into the real world with actual data from Lighthouse Labs’ Student Outcomes report.

Salary Range for Data Science Professionals

The average starting salary for those in the data science profession is $56,505 with the opportunity to start at a maximum of $110,000 per year. These numbers are based on reports from the 2021 graduates of Lighthouse Labs bootcamps, with the 90th percentile reporting earnings of $72,900 in their first year.

How to Start a Career in Data Science

Beyond studying to complete a bachelor’s degree in physics, mathematics, or computer science, you can start a career in data science through online courses such as Lighthouse Lab’s Data Science bootcamp course.

Even a degree in economics, accounting, or business can help build the foundation you will need to excel at a data science-specific bootcamp. And if you have experience in a current career role, this type of workforce experience will also help you succeed if you choose to change your career and become a data scientist, data analyst, or machine learning specialist.

Data Science bootcamp graduates are equipped with skills to start a career in data, typically as a junior data scientist or data analyst with opportunities to advance into more senior roles such as a data scientist, senior data scientist, senior data analyst, data systems developer, machine learning engineer, DataOps engineer, business intelligence developer, and data systems analyst.

Start pursuing a career in data science with Lighthouse Labs Data Science Bootcamp.