Data scientists are leading the way in how companies operate and make decisions. They apply statistical analysis, as well as computer and information science, to large sets of information. By pursuing this career path, you’ll use scientific methods to examine and analyze vast quantities of data. A data science career path begins with education that develops your data science skills and teaches you how to apply that knowledge to real-world applications.
Why pursue a career in data science?
A career in data science is resilient in the face of increasing automation. You’ll be leading changes that could affect marketing, sales, operations, project management, business intelligence, and much more.
Big data is everywhere. Businesses, nonprofit groups, and government agencies have access to unprecedented volumes of data, and if they’re able to properly manage, interpret, and act on this information, they’ll have a huge advantage over their competitors. A McKinsey & Company survey conducted in December 2018 found that 47% of respondents said that data and analytics had altered the competitive landscape in their fields, a sizable increase from the previous study’s findings. The data science entry-level salary is also quite competitive, regardless of where you live.
Some additional reasons you might consider a career in data science include:
The wide variety of work environments
Data science usage has expanded significantly in recent years. In 2020, experts in the field of big data and data science from Google and Twitter predicted that the following industries are primed for significant growth in the immediate future:
● Health care
● E-commerce and grocery companies
● Finance and insurance
Leading companies in industries ranging from marketing to logistics and health care to retail are all on board. Each of these industries is looking for opportunities to leverage data scientists’ insights.
Expanding job opportunities
As companies begin to realize how important data analysis is for their continued prosperity, they’re regularly announcing new opportunities for data scientists. In fact, data scientist was named 2019’s most promising job by LinkedIn following a 56% rise in job openings compared with the previous year. Based on the job growth statistics surrounding big data, a data science career path is high in both stability and income.
High income potential
According to 2021 data from PayScale, the median base salary of a data scientist is around $96,400. Those with five to nine years of experience earn a median salary of around $109,000, and those with 10 to 19 years in the field earn a median of around $122,000. Salaries can be affected by location, experience, and demand for the position.
Industry trends in data science
The importance of a hybrid skill set
Data scientists need a combination of soft skills and technical expertise to deliver the efficiency and output that top companies are looking for. Candidates who possess in-demand hard skills, with a particular emphasis on Python or R, are expected to be the most sought after.
Digitization and its impact
One of the most important growth skills you can develop as a data scientist is machine learning, which is expected to experience a 104% projected job posting growth by 2023. By 2024, machine learning jobs are projected to be worth almost $31 billion, reflecting a growth rate of more than 40% over a six-year period.
Areas of opportunity for data scientists
Industries with the highest levels of employment for data scientists and mathematical scientists, according to the U.S. Bureau of Labor Statistics (BLS), are:
● Computer systems design and related services
● Management of companies and enterprises
● Management, scientific, and technical consulting services
● Scientific research and development services
● Colleges, universities, and technical schools
Additionally, industries that employ a comparatively high proportion of data scientists and mathematical scientists compared with the rest of their staff include the following:
● Pharmaceutical and medicine manufacturing
● Cable and other subscription program services
The top-paying industries for data scientists include the following:
● Aerospace product and parts manufacturing
● Securities, commodity contracts, and other financial investments and related activities
● Electronic shopping and mail-order houses
Where are the data science jobs?
The U.S. cities with the highest numbers of jobs for data scientists and mathematical scientists include some of the most significant hubs for technology and government. The following cities are hailed as the top locations to pursue a career in data science:
● Austin, Texas
● Boulder, Colorado
● New York City, New York
● San Francisco, California
● Denver, Colorado
● Seattle, Washington
● San Jose, California
● Los Angeles, California
The top 10 states for data science jobs are:
● New Mexico
● New York
The locations with the highest earnings potential are Washington, California, and Maine.
According to PayScale, the median data science entry-level salary as of March 2021 is around $85,000. San Francisco-based data scientists at all levels of experience reportedly earn 28% more than the nationwide average. For prominent companies, it’s not uncommon for entry-level data scientists to earn a starting salary above $100,000. This is especially true for industries that offer higher salaries overall, including some businesses in the technology industry.
Advanced job options
Collaboration with your colleagues and the opportunity to work on specific projects may allow you to specialize or advance as a manager of data staff members, teams, or entire departments within an organization.
Average salaries according to PayScale for advanced specialized occupations related to data science, as of March 2021:
Average salaries according to PayScale for advanced data science roles:
● Senior data scientist: $127,000
● Chief data officer: $176,000
Computer systems design
Data scientists play a crucial role in developing custom solutions for clients with specific data science needs. Depending on the client’s level of sophistication, you might have to take an outcome-oriented approach and work backward to help the client develop data management solutions.
In computer systems design, you’ll be responsible for creating and installing more standardized product offerings and consulting with businesses as they implement machine learning, automation, or data visualization products.
Data scientists may work for enterprises that manage a portfolio or network of constituent organizations. In this capacity, you’ll be responsible for cleaning and reporting internal data compiled by those constituent organizations for the benefit of the management enterprise. Analyzing this data will help the parent organization make informed decisions moving forward. You may also be tasked with serving as an enterprise-sanctioned resource for the constituent organizations.
Consulting services have several different uses for data scientists. If you work for a consulting company, one role would entail in-house data science work to guide the group’s decision-making. However, you could also engage in research for client-facing staff members to help them develop data-driven recommendations. You might also work directly with the client on data science strategy or review data to provide your own professional insight.
Top skills and digital tools for data scientists
In addition to knowing the right software and programming skills, data scientists need highly developed soft skills, such as the ability to regularly translate complex concepts into simple, straight forward language.
The most sought-after skills in data science skills
These are the areas of expertise you’ll need to possess for job openings between now and 2023:
Projected Posting Growth (2018-2023)
Source: Burning Glass Technologies
Here are the specific technical skills that you’ll need to know, along with the percentage of job postings that have indicated a need for these abilities:
● SQL: 38%
● Microsoft Excel: 35.2%
● Python: 31.7%
● SAS: 30.8%
● R: 29.6%
● Tableau: 23%
● Microsoft PowerPoint: 15.5%
● Microsoft Office: 13.7%
● Data visualization: 10.2%
● Apache Hadoop: 8.8%
Soft skills in data science
Here are the most in-demand soft skills you’ll need to develop to apply for jobs as a data scientist. We’ve included the percentage of job postings that required each skill:
Data scientists with these specialized skills will be in increasingly high demand between now and 2023:
Projected Posting Growth (2018–2023)
Data Lakes and Reservoirs
Source: Burning Glass Technologies
Data science internships
Participating in an internship is a key way to enter the industry or change careers. It’s also a great way to develop data science skills. A data science internship from one of these companies could help you get your foot in the door:
In addition to your being able to connect with other professionals, membership in relevant industry groups means having access to the latest information in the field. Consider joining one of these groups if you’re interested in growing your knowledge base and learning about new career opportunities:
With highly specialized and in-demand skills, you’ll have the opportunity to be a leader in the big data environment. As a data scientist, you’ll turn raw numbers into actionable insights and help businesses make a bigger impact. Embark on a data science career path today. We’ll be your guide.