Overcoming Imposter Syndrome as a Data Scientist

It is common for data scientists to think they are pretenders or frauds. Even talented experts sometimes doubt their skill level and some aspiring data scientists may read a job posting and feel that data science is not for them.

If you feel like you’re less knowledgeable or lacking the expertise that your colleagues have, then you might have imposter syndrome. As with many fields, it is common to see imposter syndrome in data science. This article will explain what impostor syndrome is and provide tips on overcoming impostor syndrome in data science. 

What Is Imposter Syndrome?

The American Psychological Association (APA) defines imposter syndrome as a constant feeling of self-doubt, insecurity, and incompetence. The term was first coined by psychologists Pauline Clance and Suzanne Imes in the 1970s in a study about high-achieving women who experience self-doubt in their industries.

The APA further states that feelings of imposter syndrome happen when you believe that you are inadequate and lack the necessary skills despite your academic and professional achievements. Despite evidence of your skills, you attribute your success to luck. It can manifest regardless of gender, social status, work background, and expertise. 

Is Imposter Syndrome Common in Data Science?

Yes, imposter syndrome is common in the field of data science. Many data scientists attribute it to the newness and scale of the profession. A successful data scientist might have had experiences in a different science role in the field of statistics, computer science, engineering, or business before beginning a career in data science. 

According to the University of New South Wales, the data science industry continuously evolves and shifts as new fields of study, software, languages, technical skills, and new demands emerge. This can add to the fear of failure and judgment that data scientists in this field may feel while trying to keep up with the ever-changing industry. 

How Imposter Syndrome Affects Data Scientists

Burnout

People who have impostor syndrome in data science will feel that they cannot keep up with the demands of the job. Whether they deal with deep learning models or solve issues with privacy policies, someone with imposter syndrome will experience the cycle of fear of being found out as a fraud. This leads them to invest more time and effort, leaving no room for rest and self-care. 

Loss of motivation 

As mentioned, data science is a relatively new field with many people discovering cutting-edge research and new technologies. It can be overwhelming for someone who is experiencing a feeling of inadequacy. The more learning tools and data science resources are available, the more overwhelming it can be to try to keep up. 

Poor job performance 

Being constantly on edge about your skills will affect your mental health and may spill onto your job performance. People with impostor syndrome often feel they lack knowledge because they don’t know everything there is to know about data science. 

What Causes Imposter Syndrome?

Demands of the job

Data scientists work in high-pressure and fast-paced environments. The shifting of technologies around machine learning and deep learning algorithms is a continuous process. Not knowing everything there is to know about data science keeps you in a mindset that you are not good enough. It then becomes a loop as you learn new things each day.

Success

The more knowledgeable and experienced a data scientist is, the more likely they are to experience a bit of imposter syndrome. Successful data scientists have developed strong domain knowledge and are more familiar with the challenges of the field. They also know what knowledge gaps they need to address. 

If you are in this science position, you are aware of the common questions. It will lead to more questions about your competency and whether you are a real data scientist. The more complex a project becomes, the more you fear failure. 

Data science is a new field

Many data scientists have had previous experiences in different science industries. Being a new field, some people who become data scientists feel that they don’t have the proper education or training. However, what matters is hands-on experience in solving real-world problems. 

What Imposter Syndrome Looks Like in the Workplace

Dr. Valerie Young, in her book The Secret Thoughts of Successful Women: Why Capable People Suffer from the Impostor Syndrome and How to Thrive in Spite of It says imposter syndrome is classified into five types. Listed below are the five types and how they might manifest in the data science workplace.

• Natural Genius: Natural geniuses don’t deal with challenges well. These types will give up easily when they encounter a skill they can’t learn immediately or an algorithm problem that they can’t solve. 

• Perfectionist: Perfectionists in the workplace set unrealistic goals for themselves but have too much self-doubt to allow themselves to achieve these goals. Perfectionist data scientists have difficulty delegating tasks and taking risks. They feel frustrated and disappointed if their knowledge does not meet the problems in front of them.
• Superhero: Superheroes push themselves to work extra hard because they fear that even a small failure or lapse in productivity will expose them as undeserving of their position on their team. This may lead to overworking, burnout, and poor work-life balance. 
• Individualist: Individualists refuse to ask for help because they believe it makes them seem weak and incapable. They turn down assistance because they think it lessens their worth to the team. This can lead to mistakes. 
• Expert: Experts believe that they got their job due to luck or trickery. Some may even be hesitant to call themselves data scientists or compliment themselves for fear of being labeled as arrogant.

Data scientists and machine learning engineers who have impostor syndrome always feel like everyone else is more qualified and that there has been a mistake in the hiring process. It will lead to them being afraid to take risks and pursue more complex projects despite their proven ability and praise from team members and management. 

Can Imposter Syndrome Be Cured?

Yes, much like all negative feelings, impostor syndrome can be cured. You can overcome imposter syndrome and begin to appreciate all your accomplishments. There are various ways to conquer imposter syndrome in data science listed below.

Overcoming Imposter Syndrome in Data Scientists

Understand that it is impossible to know everything

The root of imposter syndrome in data science is not knowing everything. However, in real life, it is impossible to know everything. Learning is an ongoing process. Those you perceive as “real data scientists” did not reach the 100th step without going through the first 10 steps. 

Ask questions

Data scientists work on collaborative projects. A bit of fear can derail the whole project if you don’t ask questions. Data scientists are navigating a complex, multi-faceted field. Your peers and more experienced people on the job can help you gain more knowledge through conversation and professional advice. 

Have a growth mindset

Your professional growth in the field of data science relies on the mindset that you bring to work every day. If you continuously feel that you will fail in every task because of your knowledge gaps, you will get stuck and have a tough time understanding the domain knowledge you need to know.

Share your knowledge

Data scientists learn from each other. When you discuss what you’ve learned with your peers, you can gain a new perspective. Through the feedback and questions, you can develop a more comprehensive understanding of a subject. It also helps in your collection of domain knowledge.

Upskill regularly

Gaining certifications, learning new tools, and building your data science portfolio can help your confidence as a data scientist. There are a lot of data science books to read and you can complete data science projects for beginners to master the basics. Continue to scour the Internet for alternative learning platforms to gain more knowledge. 

How a Coding Bootcamp Can Help You Get Over Imposter Syndrome

A coding bootcamp can help you overcome imposter syndrome because you will learn new things and address skill gaps. The Metis Bootcamp will help you learn data science skills even on a busy schedule. You can also check out the best data science bootcamps that can help you get an advantage in data science and other adjacent fields. 

Can Imposter Syndrome Be a Good Thing?

Yes, there are moments when having imposter syndrome can be a good thing, especially if you put in the work towards overcoming it. Below are reasons why it can be good or bad for data scientists to experience imposter syndrome.

Why Imposter Syndrome Is Good

• You learn to recognize negative thoughts. Part of becoming a data scientist is separating feelings from thoughts. Having imposter syndrome may help you make more logical distinctions to projects.
• You become motivated to become a real data scientist. Feeling inadequate about your skills can make you work harder to prove yourself. Imposter syndrome can motivate you to always do a good job with the hope that your colleagues recognize your talent instead of seeing the fear within you. 
• Imposter syndrome indicates that you are successful. Those with imposter syndrome are usually successful people. This psychological experience often occurs during a promotion or when you land a new job.

Why Imposter Syndrome Is Bad

• It can cause depression. The feeling of otherness within your team can make you feel on edge about your abilities. It can also sometimes lead to anxiety and depression when not addressed.
• You don’t take credit for your work. Data scientists with imposter syndrome are afraid to take credit for their work. They are afraid that people might discover that they are not knowledgeable and not a “real data scientist.”
• You might self-sabotage. Data scientists with imposter syndrome are scared to ask for help from their peers. This leads to more burnout and unproductive outputs, which may harm your career growth.

Don’t Let Imposter Syndrome Hold You Back

While imposter syndrome can have negative effects, there are various ways to overcome the feeling of not being good enough. Continue to upskill through online programs such as Coding Dojo. Data science is a knowledge-active field. If you are struggling with self-doubt, training with the various courses and programs in data science may help you gain more confidence. 

Keep working to master relevant programming languages if you are trying to start a career in data science. Ask the basic questions to have more accurate insights into the field. If you are employed, taking the tips mentioned can help you gain more business insight and career advice.

Imposter Syndrome in Data Science FAQ