Common Challenges in Data Science Careers and How to Overcome Them

Data science has become an increasingly integral—and profitable—tool for many businesses. According to a 2023 survey from the consulting firm NewVantage Partners, 91.9% of companies have gained measurable business value from investing in data and analytics.¹ From data mining and organizing huge data sets, to creating visuals and presenting to business executives, organizations need teams focused on sourcing, cleaning, analyzing, and interpreting information that can help them make better business decisions.

This success has contributed to a surge in demand for data scientists. In fact, the U.S. Bureau of Labor Statistics predicts that employment of these professionals will increase by 35% between 2022 and 2032. And since demand has grown so much, so have the salaries—the average salary for a data scientist is $103,500.²

While there are more opportunities than ever in data science, it’s still normal for professionals to encounter obstacles in this field. The challenges faced by data scientists are also more nuanced and change more rapidly since the discipline is relatively new.

If you're interested in this career path, it's good to be prepared for what may come your way. This post will explore common data science career challenges and outline effective strategies to overcome them.

Getting Your Start

Starting your data science career can be an exciting but daunting process. Data scientists have many responsibilities, such as collecting and analyzing data (sometimes from multiple data sources), programming machine learning algorithms, creating predictive models, and explaining all of that to business stakeholders.³ Many of these tasks require in-depth knowledge of computer science, statistical methods, and software engineering.⁴ Additionally, technologies like artificial intelligence (AI) and data visualization software often have steep learning curves.

You can gain foundational data science knowledge by earning a bachelor’s degree in data analytics, computer science, engineering, mathematics, or a related discipline. Many colleges and universities also offer master’s in data science programs, and even some that are online for increased flexibility.⁴ Rather than a short-term bootcamp or certificate, a formal degree program provides a structured learning environment to develop essential knowledge and skills.

Changing Careers

Changing into a data career from somewhere else can be difficult, but it's not impossible. For example, many employers expect data science job candidates to participate in rigorous and time-consuming technical interviews. Some people may also experience imposter syndrome, which is the fear that they don’t have the skills or talents to land such a rigorous and impressive job.⁶

You can overcome these challenges by seeking mentorship from experienced data professionals. They can provide insights into the job market and help you identify necessary skills. They also can help you identify improvements by reviewing your resume, portfolio, and applications.⁷

Job Market Demands

Rapid technological advancements have led to numerous job market challenges. One of these challenges is that skills requirements have evolved rapidly, leading to a widening talent gap. For instance, many companies are seeking employees who can use AI and ML for data security, but the demand for this skill has outpaced supply.⁷ Data science has also become increasingly competitive, making it more difficult for applicants to stand out.⁶

There are many ways to gain in-demand skills and make a strong impression on potential employers. First, browse advertisements for data science jobs to identify essential skills and tools. Machine learning, cloud data management, data storytelling, and programming languages are common in these job descriptions. Next, seek opportunities to gain these competencies. Professional organizations like the Association of Data Scientists offer online courses, certifications, and peer-reviewed publications about the latest data science techniques.⁸ New York Institute of Technology also offers an online Master of Science in Data Science that you can complete in as few as 10 months.

The Job Search

Given the skyrocketing demand for data scientists, you might assume that you can easily land your dream job—but that’s not always the case. Aspiring data professionals frequently find the job search to be daunting and time consuming.

Choosing the right career path is one significant obstacle. There are many roles in data science, including data architects, data storytellers, predictive modelers, and statisticians. These professionals have some overlapping skills but manage different aspects of the data science pipeline (e.g., someone might work on data preparation while another builds charts and graphics for a presentation to non technical stakeholders). Developing a versatile skill set can expand your career opportunities.⁹

Beginning data science professionals may also find it challenging to showcase their skills in the right ways. Creating a portfolio of real-world data science projects can help you demonstrate your abilities to potential employers.⁹

Skill Gaps

Even the most experienced tech professionals can experience a skill gap. This field continuously changes, so it’s easy to fall behind if you don’t keep up with the latest trends. According to Gartner, the latest trends in data science include:¹⁰

• Edge AI: By 2025, over 55% of data analysis by deep neural networks will happen at the “edge,” or the moment the data is created
• Cloud data ecosystems: Companies increasingly store information in cohesive, cloud-native data ecosystems instead of self-contained software

Data scientists can adapt to these changes and bridge skill gaps by proactively learning about innovations and trends. Conferences, online courses, and data science forums provide opportunities to gain new knowledge and skills. You should also subscribe to newsletters, podcast, and news alerts on major data science trends.

Work-Life Balance

Data science jobs can be demanding and stressful, especially if you’re trying to complete projects on tight deadlines. You might find yourself working long hours, performing time consuming audits of confidential data, or answering emails late at night. But most data scientists find immense satisfaction in the work that they do. Few people possess the skills that they do, and uncovering data generated insights can feel like solving a puzzle, or creating a map through uncharted territory.

You can overcome work-life balance challenges by scheduling specific time slots for routine tasks, such as checking email and returning calls. Communicate your progress frequently and flag blockers. Set firm boundaries between your home life and work, and review your achievements daily to ensure you’re on track to meet your goals.¹¹

Career Burnout

According to a 2021 survey by Data Kitchen, 97% of data engineers experience burnout due to unreasonable demands from employers, work-life balance disruptions, and other obstacles.¹² Burnout can come in the form of exhaustion, lack of motivation, and lack of interest in work.

You can address burnout by using automation to streamline manual processes, allowing you to spend more time on innovative tasks. Taking frequent breaks can also help you stay energized and enthusiastic.¹³ Don't suffer in silence; let your colleagues and manager know when you feel yourself getting overwhelmed.

Career Plateau

It’s normal to feel like you’re in a career rut after you’ve gained a few years of experience. You might get passed over for promotions, accomplish all your goals, or feel bored by your work routine.

You can navigate career plateaus by clarifying your professional goals and envisioning your future. Where do you want to be, and what will get you there? It’s also beneficial to broaden your horizons by learning new skills, expanding your professional network, and asking for more challenging projects.¹⁴ Reach out to other data scientists to see how they have navigated similar situations.

Invest in Your Future and Overcome Career Challenges

Accelerate your career by pursuing an Online Data Science, M.S. at the New York Institute of Technology. Our expert faculty teaches the latest data science tools and techniques so you can stay on top of innovations in the field. You’ll develop advanced technical skills as you take rigorous courses on big data, machine learning, data visualization, and other topics. Our electives also enable you to develop expertise in desirable niches, such as cybersecurity and information security.

Get in touch with an admissions outreach advisor today to learn more.