Covid and the Great Resignation Have You Rethinking Your Job Too? Many Workers Are Turning to Data Science

The Harvard Business Review called the role of data scientist the “sexiest job of the 21 century,” and this has become even more true now that Covid has pushed additional aspects of society online. Since the pandemic, there has been a shift to online and remote work that appears to be here to stay. With an average salary of $100,560 for data scientists, according to the US Bureau of Labor Statistics, many workers are turning to data science to build their future careers and find many opportunities. 

The US Bureau of Labor predicts that data science will grow more than almost any other field through 2029. Today, a search for ‘data science’ jobs on LinkedIn in the United States alone leads to just under 180,000 job postings and more than 40,000 job postings on Indeed.com—two leading job portals. The total number of postings is expected to keep growing as well. The US News and World Report projects 31.4% employment growth for data scientists from 2020 to 2030, indicating even further growth in the sector over the next decade.

One important thing to note is that a career in “data science” can mean many different things and may indicate various positions. The opportunities range from data scientist to data analyst roles, requiring slightly different skills. The World Economic Forum ranks the top 10 positions in order under emerging roles in the data and AI data career cluster: 

#1 – Artificial Intelligence Specialist

#2 – Data Scientist

#3 – Data Engineer

#4 – Big Data Developer 

#5 – Data Analyst

#6 – Analytics Specialist

# 7 – Data Consultant 

# 8 – Insights Analyst 

#9 – Business Intelligence Developer 

#10 – Analytics Consultant 

The World Economic Forum (WEF) also reports that because data science and AI are growing industries, they continue to push boundaries for interested individuals. Furthermore, as data science is considered an emerging profession, it may “present more opportunities to break into these frontier fields,” and “such transitions do not require a full skill match between the source and destination occupation.” 

An ability to transition into data science without having a full skill match is excellent news for those working as research analysts, academic researchers, or other adjacent roles interested in transitioning into data science roles. With an adjoining position and the support of Data Incubator’s data science bootcamp, you could be ready to apply for a lucrative data science role in as little as eight weeks. 

Has Covid Changed Online Learning Trends? Our Sources Say a Resounding Yes 

One outcome of the Covid pandemic has been an increase in online learning. According to the World Economic Forum, online learning courses more than doubled in 2020 and increased in 2021 by 32%. In another historic moment, online MBA programs overtook residential, in-person MBA programs for the first time in the academic year of 2020-2021. 

Importantly, employers have become more accepting of online credentials over the years, particularly since the pandemic, with 55% not seeing any difference between an online credential and one obtained through an in-person program. This bodes particularly well for receiving a data science credential as you consider transitioning into data science. A credential opens up an entire online training world, from bootcamps to longer-term credential degree programs. 

Are Academic Research Associates Leaving Academia for Data Science? 

Even academia doesn’t appear to be immune to the great resignation. With the hashtag #leavingacademia growing in popularity, many academics and university employees are evaluating different opportunities within the industry. Additionally, Nature published a 2021 salary and career satisfaction survey and found that “respondents in industry (64%) are much more likely than those in academia (42%) to feel positively” about their career prospects. 

Additionally, later-stage career researchers were less likely to see a positive outlook: 39%, compared to 49% with early or mid-career researchers. For such researchers, data science is a prime candidate for academics to evaluate for a transition to industry, specifically research associates, given their role’s methodical, data-focused and investigative nature. 

For academic researchers and early academics, the dropout rate has increased dramatically. One study by Indiana University found that 50% of academic scientists were leaving the academy after just five years. It also cited a study in the National Academy of Sciences journal that reported a growing “temporary workforce” in academia. It found that 60% of academics are likely to hold supporting scientist, research associate, and lab technician roles for the entirety of their career compared to just 25% some 50 years ago. 

Data science can be broken into four key aspects: data collection, data cleaning and transformation, statistical analysis and data visualization. Depending on your experience as an academic researcher, you may already have expertise built up on one to all four key aspects of data science. Key strengths you likely already have as an academic are research, critical thinking and data assessment, while key weaknesses to address may include speed, language familiarity and performance expectations. 

If you want to transition from academia to the data science industry, you are certainly not alone. Several Data Incubator alumni have also transitioned to industry into data science roles. Check out the following blog series for more detailed stories that profile our past academic alumni:  

• The First 4 Steps to Transition out of Academia into Industry
• 7 Early lessons Alumni learn When Leaving Academia
• What it was Like Leaving Academia

There are significant job opportunities in data science for current academics and a higher propensity to enjoy a data science job in the industry. Next, you need to identify the right option.

Data Science Opportunities: So, how can you move into the data science industry? What skills do you need? And what even is data science? To evaluate potential opportunities, you need to search all online job portals from LinkedIn to Indeed.com to see the sheer volume of data science roles available. Open positions range from analyst, statistician, visualizer, developer and more. 

Job Portals: Start searching for data analyst and scientist roles on top job boards, including LinkedIn, Indeed.com, Glassdoor, and by searching directly at companies you are interested in. Look closely at the requirements, tailor your resume and cover letter accordingly and identify what missing skills you may need to hone to become a top applicant for the selected role. You may find several exciting opportunities you are interested in but are not yet quite prepared for during your search. At this stage, The Data Incubator comes in to support you. The Data Incubator puts on various bootcamps to prepare you for the perfect role!

Bootcamps: Data Science bootcamps are a fantastic way to improve your chances of obtaining a coveted data science position. The Data Incubator offers an immersive eight-week data science bootcamp that prepares you for real-world data science positions, a data engineering bootcamp, and a data science essentials part-time online program for individuals with part-time availability. Not only will the curriculum be world-class, but you will have the opportunity to work with a career coach, network with other data scientist trainees and showcase your newly honed data skills. 

Want to learn more about how to evaluate and select a Data Science bootcamp? Check out our other blog post, “What the Best Data Science Bootcamps Have in Common,” for more information on content evaluation, options, financing, scholarships, and more. 

Finally, The Data Incubator insights blog is a great resource to continue your research and explore if data science is the right fit for you.