With the rise of big data, the role of data scientist has become one of the most in-demand jobs of the 21st century. However, as more and more people flock to data science as a career, some are wondering if the job market is becoming oversaturated. Is it still relatively easy for qualified candidates to find data science jobs, or has it become difficult to stand out?
In this article, we’ll examine the current data scientist job market, looking at factors like salary, required skills and experience, job availability across industries, and projected growth. We’ll analyze data and trends to determine how competitive the data science field really is and what it takes to launch a successful data science career today.
The Growing Demand for Data Scientists
First, there is no question that demand for data scientists has exploded in recent years. As data has become an increasingly important asset for companies and organizations across all industries, hiring for data-driven roles has skyrocketed.
According to LinkedIn data, the number of data scientist job postings increased by over 650% between 2012 and 2019. Job search site Indeed also reported a 344% increase in data science job postings between 2015 and 2019 alone.
This enormous growth in demand is driven by the rise of big data and the urgent need for skilled professionals who can analyze large, complex data sets and deliver actionable insights to inform business strategy and decision making.
As long as companies continue to rely on data analytics and AI to optimize operations, user experiences, marketing efforts, and more, demand for data science skills will remain high. Even roles outside of dedicated data science jobs are increasingly requiring data analysis and modeling skills.
Data Scientist Salaries Remain Strong
Along with rising demand, another indicator of a strong job market is competitive salaries. Here again, data science jobs deliver.
According to PayScale, the average salary for a data scientist in the US as of March 2022 was $96,462 per year. However, data scientists working in major tech hubs and large cities can make upward of $130,000 annually.
| City | Average Data Scientist Salary |
|---|---|
| San Francisco | $136,118 |
| Seattle | $130,873 |
| New York City | $124,647 |
| Boston | $121,177 |
| Los Angeles | $120,365 |
PayScale reports that the average annual pay growth for data scientists is 4%, so salaries in the field continue to rise steadily. Even at the entry-level, the median salary for data scientists with 0-1 years of experience is around $85,000.
Generous compensation reflects high demand for data science skills. Employers are eager to attract and retain top talent in this competitive landscape.
What Skills Do Data Science Jobs Require?
To successfully land one of these lucrative and in-demand data science jobs, candidates need to possess certain credentials, technical abilities, and soft skills.
Here are some of the key requirements for data scientists today:
Education
– Advanced degree (Master’s or PhD) in a quantitative field like statistics, mathematics, computer science, analytics, or data science
– Bachelor’s degree in a STEM field may be sufficient for some entry-level roles
Technical Skills
– Expertise in statistical and data modeling techniques, including predictive modeling, machine learning, algorithms
– Programming – especially Python and R
– Working with big data platforms like Hadoop, Spark, cloud tools
– Data wrangling, mining, visualization tools
– SQL database skills
Soft Skills
– Communication and presentation abilities
– Business acumen
– Translating data insights into actionable business recommendations
– Creativity and curiosity
So while the technical skills are very important, data science also requires soft skills and business strategy knowledge to turn analysis into impact.
Data Science Jobs Span Many Industries
One advantage for those looking to enter the data science field is that these jobs span practically every industry vertical.
While tech companies were early adopters of data science capabilities, all types of organizations now use data to drive competitive advantage.
According to LinkedIn data, some of the top industries hiring data scientists today include:
– Information Technology and Services
– Financial Services
– Computer Software
– Internet
– Higher Education
– Marketing and Advertising
– Management Consulting
– Government Administration
– Online Retail
– Health Care
Data science job postings increased across all these industries from 2015 to 2019. This variety provides more career options and flexibility for data science professionals. Those with specialized domain expertise in fields like finance, healthcare, ecommerce or others may find abundant data science job opportunities in those sectors.
Projected Job Growth for Data Scientists
Not only are data science jobs in high demand today, but the future looks very bright as well. The U.S. Bureau of Labor Statistics projects 27.9% growth for data science related roles from 2019 to 2029, much faster than the average for all occupations.
Specifically, here are BLS growth projections for some common data science job titles:
| Role | Projected Growth (2019-2029) |
|---|---|
| Data Scientists | 31% |
| Statisticians | 35% |
| Operations Research Analysts | 25% |
| Database Administrators | 11% |
| Software Developers | 22% |
The massive amounts of data generated today show no signs of slowing, which means skilled data professionals will continue to be in high demand.
According to an IBM study, the projected number of data science jobs listings will increase by 28% to 2.7 million postings by 2020 – a sizeable jump from 2.2 million positions in 2018.
As long as organizations rely on using data to improve products, services, processes and customer experiences, data scientists will play a critical strategic role. Candidates who stay up-to-date on the latest data tools and technologies should have their choice of data science career opportunities.
How Can Candidates Stand Out?
Given the highly competitive landscape, data science job seekers need to demonstrate key qualifications to attract recruiter attention and secure offers. Here are some tips:
– Obtain advanced degrees in technical fields to confirm your quantitative and analytical abilities. Specialized Master’s like MS in Analytics offer great ROI.
– Develop expertise in statistical modeling and hands-on tools like Python, R, SQL, Hadoop, Spark. Pursue certifications to validate your knowledge.
– Build a portfolio of data analysis projects and be able to present examples and discuss your methodologies to solve problems.
– Highlight both your technical depth and your business strategy/communication skills.
– Network extensively within the data community and connect with recruiting managers at target companies. Attend data conferences and events.
– Consider data science bootcamps or online courses to quickly gain skills if you are transitioning from a different background.
– Show passion and curiosity for working with data, solving complex problems, and translating analysis into business impact.
Conclusion
In summary, data science remains a promising and exciting field with high demand, competitive compensation, abundant growth and career options across industries. However, it is very competitive and candidates need to work diligently to demonstrate the right blend of technical and soft skills.
For those with the required credentials, skills and experience, data science offers a career path with immense opportunity. By excelling at both the analytical and strategic aspects of the role, talented data scientists can create significant value for employers while building a rewarding and lucrative profession.
