Data-centric Job Sectors Expanding Opportunities for Data Analysts and Data Scientists
In today's data-driven world, the demand for data scientists and analysts is skyrocketing, with a strong need for these professionals across various sectors such as IT, banking, finance, insurance, healthcare, and e-commerce.
Data scientists are highly sought after due to the increasing use of AI and machine learning. According to career outlooks, employment of data scientists is projected to grow significantly, with an expected increase of 36% from 2023 to 2033. Mid-level data scientists can earn between $110,131 and $123,925, while senior-level positions range from $127,981 to $141,082.
Data analysts are also in high demand, with growth expected across similar industries. Data analyst jobs are projected to grow by 23% from 2023 to 2033. Salaries for data analysts vary by experience but generally fall between $71,000 and $119,000 annually.
Both roles find key opportunities in cities like Boston, San Francisco, and Vancouver for data scientists, and similar hubs for data analysts. Industries such as finance, IT, and scientific services tend to offer higher salaries for data analysts.
The healthcare industry is one of the top industries hiring data scientists and analysts, with companies like Change Healthcare, Centene Corporation, and the National Health Service (NHS) needing data professionals. The retail industry also utilises data analysis to better understand consumer behaviour and improve marketing and sales strategies, with companies like Walmart and Amazon hiring data analysts and data scientists.
Universities like the University of California, Johns Hopkins University, California State University, Washington University in St. Louis, University of Pennsylvania, Carnegie Mellon University, University of Utah, Stanford University, Columbia University, Emory University, University of Texas, University of Southern California are top employers for data scientists and analysts.
To qualify for an entry-level data analyst job, one needs a bachelor's degree or a bootcamp or certificate in data analytics. For high school graduates, more companies are considering candidates without college degrees, but they need an immersive reskilling program to learn SQL, Excel, and Tableau.
To land a data analyst job, one needs to demonstrate skills in data management, statistics, communication, visualization, Python, and PowerBI. For current data analysts, taking on challenging projects, showing curiosity, asking questions, and improving Python and applied statistics knowledge can help move up to a data scientist role.
For career changers, identifying industry skill gaps and reskilling is necessary to become competitive. Updating the resume and optimising profiles, researching companies hiring data analysts, and networking with people at those companies can help. Seeking out internships or apprenticeships in data analytics, or volunteering with a nonprofit can also help college graduates land a data analyst job.
The U.S. Bureau of Labor Statistics projects a 36% increase in data science jobs by 2031. Interestingly, 18.4% of data analysts don't have a bachelor's degree. For career changers, making a list of transferrable skills, taking a data science course while working full-time, and reading a guide on explaining career changes during an interview can help land a data scientist job. Connecting with people who work in data science or at the companies one is targeting through the alumni network can also help college graduates land a data scientist job.
In conclusion, the demand for both data scientists and data analysts is strong across various industries, driven by the increasing need for data-driven decision-making. With the right skills and determination, opportunities for these roles are abundant and promising.
- To further enhance one's career prospects, taking advantage of the alumni network can be beneficial for those seeking career change, particularly in the fields of data science or cybersecurity training.
- In light of the growing demand for data scientists, those with an educational background in finance, business, technology, or education-and-self-development may find fruitful opportunities to transition into data science roles.
- For individuals seeking career change in the realm of data analysis, understanding the specific skill sets needed, such as data management, statistics, communication, and Python, can pave the way to securing a job in various industries including finance, IT, healthcare, and retail.
- Engaging in technology-focused training programs like cybersecurity or data science, either in universities or in the form of bootcamps or certificates, can open doors for career changers who want to enter the ever-expanding and high-demand digital landscape.
