Undoubtedly, the field of data science is one of the fastest-growing and promising career paths.

The abundance of data in almost every industry and the increasing job opportunities create fertile ground for growth and innovation.

However, it is a fact that there are not enough women in the field of data science.

Therefore, women need to be encouraged to enter this competitive field with the help of 8 success tips for women data scientists.

In today's article, we will explore:

 The role of a data scientist

 8 success tips for women data scientists

Let's start with the basics.

 What is the Role of a Data Scientist?

Data scientists are professionals who deal with the collection, analysis, and interpretation of large volumes of data (Big Data) to gather insights for better-informed decision-making.

They have knowledge in statistical analysis, machine learning, and data visualization techniques.

They are also proficient in popular programming languages such as Python and R. Data scientists can work across a wide range of industries, including marketing, healthcare, and financial analysis.

Now, let's focus on the 8 success tips for women data scientists.

 8 Success Tips for Women Data Scientists

According to the U.S. Bureau of Labor Statistics, employment for data scientists is projected to grow by 36% by 2031, much faster than the average for other professions.

However, the number of male data scientists significantly surpasses the number of women in the field.

Therefore, we have compiled some success tips that will help you if you are starting your career as a data scientist and facing obstacles and challenges.

   Seize Networking Opportunities

First and foremost, it is essential to surround yourself with the right team and expand your network with individuals who will support your decisions and provide valuable experience that you may not possess as a beginner.

After all, experience and specialization come with time.

Therefore, try to network with other members of the data team in your company, and with the appropriate support, you will make significant progress.

   Don't Settle for Less in Terms of Salary

It is a fact that female data scientists earn significantly lower salaries than their male counterparts.

According to research by O'Reilly Media, the salaries of women data scientists amount to 84% of the average salary for men, regardless of education or job title.

For example, at the executive level, the median salary for women was $163,000 compared to $205,000 for men, resulting in a 20% difference.

It is important, therefore, to negotiate your salary based on your skills and the hours you work in a company.

   Build Strong Knowledge Foundations

Knowledge is power, so it is beneficial to stay updated on the advancements and new trends in data science.

In today's era, there are a plethora of resources available on data science, including books and courses on Python, which is an essential tool and skill for your work as a data scientist.

   Draw Inspiration from Other Women Data Scientists

Through networking efforts and participation in seminars and technology events for data scientists, you can gain inspiration from other women data scientists.

Additionally, there is a wealth of online sources featuring successful women that you could have as role models.

Specifically, the field of FemTech, where many women data scientists work, is particularly emerging and has great potential for growth.

Furthermore, creating a professional profile on LinkedIn would be especially helpful.

An example of a LinkedIn profile to follow and draw inspiration from is the following:

As we can see, this is Cassie Kozyrkov, who serves as an inspiration, with numerous achievements, as she is recognized as one of the Top Voices on LinkedIn and is the Chief Decision Scientist at Google.

   Focus on Communication

Developing communication skills is one of the essential soft skills to succeed in the rising field of data science.

After all, hard skills such as knowledge of data visualization, programming languages, and machine learning are something that can be acquired.

However, soft skills like communication, negotiation, and problem-solving are of utmost importance for a role in the data science field.

   Find a Mentor

When starting at a new technology company as a female data scientist, you may sometimes feel isolated and struggle to find common ground and interests with your male colleagues.

Therefore, it is important to find a mentor.

You can find a female entrepreneur in the field of data science with whom you can discuss issues that concern you, such as salary negotiations, specialization, and your next moves to gradually climb the career ladder.

   Don't Let Others' Beliefs Affect You Negatively

Although data science is an excellent career choice for women of all ages, whether starting out or considering a career change, they are often negatively influenced by the beliefs of others and feel disadvantaged.

Despite the importance of this role, only about 20% of professionals in data science-related roles in the United States are women.

In the following image from Statista research, we can see the percentage of women in different parts of the world, who underestimate their abilities in the field of science in general.

It is crucial, therefore, not to be afraid to take risks and confront imposter syndrome in case you are belittled and your accomplishments are not recognized.

   Set Priorities

In the field of data science, there are many different roles, such as researchers, machine learning and AI specialists, and many others.

So, at the beginning of your career, it is beneficial to broaden your knowledge base.

This way, you will be able to take advantage of specialization opportunities later in your career, once you have decided on what suits you best and what you enjoy.

 Ramping Up

We talked about 8 success tips for women data scientists that, if followed and taken advantage of, could help you in your journey as a data scientist.

If you are excited and want to stay updated on the latest topics surrounding AI and Data Science, in general, follow us for more educational articles!