Data Science jobs are in high demand in the US and worldwide. While no current certification is required, data scientist and data analyst positions pay very well, with more than 36,000 positions available in the US for these two roles alone.
Today, we’ll look at the data science job market, the educational background required, and some valuable tips on how to find a job in this high-paying and in-demand career.
What Is Data Science?
Job titles and roles in data science vary depending on seniority but include titles such as Data Scientist and Data Engineer at senior levels and Data Analyst, Data Science Specialist, and Data Management Analyst at mid-level and entry-level positions.
Typical duties for a Data Scientist include solving high-level business problems with analytical skills using a mix of data sources, data management techniques, and analysis of large amounts of unstructured data. In this top role, Data Scientists usually have a strategic and senior management role within organizations in industry, scientific research, education, systems and software development, and government.
Data Engineers and Data Analysts tend to be data science specialists at mid-level positions and sometimes entry-level analysts. But, increasingly, data science professionals must also be able to use machine learning and artificial intelligence techniques and tools to handle the growing amount of data available.
While there is no established certification, there is a higher barrier to entry because of the need for higher-level education and experience coupled with programming, math and data software, and tools.
Education & Skills of Data Science Pros
While there are no current certifications or prerequisite training for a data scientist, research on LinkedIn shows that 98% of those hired have a bachelor’s degree or higher.
Based on job openings we surveyed, the bar for entry for Data Scientist positions is high. Employers prefer Bachelor’s or Master’s degrees, seven years or more experience, and in-depth programming and technical knowledge, depending on the role.
Data Scientists Skills
The skills highlighted most often by employers looking to hire Data Scientists include programming skills (SAS, R, Python), math and statistical skills, data visualization, Hadoop, SQL, and machine learning. In addition, management experience, communications and presentation skills, data visualization, storytelling, and solid industry experience add to the marketability and fast track for this senior-level industry role.
Data Engineering Skills
Data Engineers typically manage vast amounts of rapidly changing or unstructured data. They focus on deploying, managing, optimizing data pipelines, and crunching data for use by data scientists and senior management in solving business problems and enhancing product development and research. Programming language skills such as Java and Scala are essential, NoSQL database (MongoDB, Cassandra DB) and frameworks experience, including Apache Hadoop.
Data Analyst Skills
The skill requirements for Data Analysts vary widely depending on the industry, role, and seniority. These data science pros often work closely with business analysts to organize, manipulate and analyze data for strategic decision-making by Data Scientists and senior management. Programming skills such as SAS, R, and Python are expected, along with statistical and mathematical skills. Data Analysts also use data wrangling and data visualization to translate complex data into usable business intelligence.
Data Science Training
A university bachelor’s degree is a minimum requirement, while a Master’s degree is the gold standard for senior-level data science jobs. Short-term courses are helpful and valuable for entry-level data science positions or specific skills training and professional development.
There are three ways to gain entry into the high-paying world of data scientists. The first is to transition from a related career involving a robust data, research, mathematics, and research background. In addition, any programming skills will be an asset.
- Online courses – will appeal to those already working or in a data science-related job. These courses deliver the most up-to-date, relevant, and practical training for skills to succeed. Also, check out our comprehensive data science training by active industry leaders.
- Bootcamps – provide a faster way to get direct training and technical skills through intensive six-month programs. They are expensive but often offer job placement, internships, and other job-finding assets.
The growth of machine learning impacts both the job and the skills needed to be a high-level Data Scientist. To compete in the data science profession, you will need lifelong learning skills and continual updates to new software and tools as they’re introduced. Adding these to your resume or portfolio will enhance your marketability.
Data Science Job Market
Job openings in the data science profession have increased by 46% since 2019, according to LinkedIn. Salary.com showed 107,406 current jobs for “data scientists” and 210,931 for “data analysts” in the US.
US Bureau of Labour Statistics (BLS) estimated 105,980 data scientists employed in the US with an average salary of $108,860 in 2021. However, wages are much higher in large cities and Silicon Valley and lower in non-metropolitan or Midwest US locations.
Glassdoor had 10,537 open positions for Data Scientists in the US, with another 25,724 openings for Data Analysts, and 6,957 for Data Engineers.
Data Scientist Salaries
Because data science is a highly-specialized, high-demand position, salaries are attractive and increasing quickly. LinkedIn shows average salaries for Data Scientists ranging from $100,000-$130,000 and up.
UC Berkeley highlighted average salaries for Senior Data Scientist at $142,298, followed by Data Scientist ($117,212), Data Engineer ($112,493), and Data Analyst ($69,517).
How to Find a Job in Data Science?
In the competitive marketplace for data science professionals, you’ll need to stand out as a candidate. Here are some tips to help you rise to the top of the resume pile with potential employers:
- Credentials – make sure you highlight the specific experience and technical skills advertised for the position
- Portfolio – a project portfolio or portfolio website helps you stand out and demonstrates both knowledge and communication skills
- Technical skills – highlight your most valuable technical skills and any related certifications in programming, data security, machine learning; make sure to include any additional professional development and online courses you’ve taken, such as those at Legends of Tech
- Resume – highlight data-related jobs or skills such as data analyst or business analyst if you’re looking to advance to the senior data science positions.
Job Searching Tips
Because of the higher barrier to entry and competition for data science jobs, face-to-face meetings are an additional way to stand out from other candidates. Look for local meetups, events, and conferences to network and raise your professional profile.
When looking at potential employers, target growth companies more willing to provide entry-level opportunities if you have less experience. Keep up with the latest trends and industry developments, particularly machine learning and artificial intelligence.
Ready for a Career in Data Science?
We hope this overview of data science jobs was useful and puts you on track for a career in this high-paying, fast-growing industry. With the right education, skills training, and experience, you’ll quickly be on the fast track to bigger things. We’ve got other valuable Legends of Tech data science training and resources, including our popular blog. Join us and move your career forward faster.