Women in Tech Series: Data Science
In the tech sector, women have historically been underrepresented. Nonetheless, there is a growing push to encourage more women to work in technology and thrive in it. Nowadays, there are many clubs and projects supporting women in technology, such as networking groups, mentorship programs, and scholarships.
The underrepresentation of women in the IT industry is rooted in a variety of reasons, including prejudice and preconceptions, a lack of mentors and role models, and structural hurdles. Boosting diversity in the tech sector is not only fair but it has been proven to produce better results, including increased creativity and innovation.
In order to encourage more women to enter the field, it's critical to reduce the institutional and cultural hurdles that prevent entry and promotion in the tech sector. This entails supporting equal compensation, adaptable work schedules, and inclusive workplace cultures in addition to encouraging STEM education for young girls and women. We can ensure that women are adequately represented and valued in the tech sector by adopting these steps.
In this blog series, we acknowledge women who have made an impact in different fields of tech, starting with data science.
Women in the field of data science have also been historically underrepresented. However, numerous programs and organizations are trying to change this.
Image Description: Three women working over a desk.
Data science involves using statistical methods as well as computational methods to extract insights from large amounts of data. As data science becomes more and more important in many industries, there is a growing demand for skilled scientists. However, despite their need for them, women are still underrepresented in the field of data science.
Several efforts and organizations promote women in data science in an effort to close the gender gap. For instance, Women in Data Science (WiDS) is a global organization that provides mentorship, networking opportunities, and educational resources to women working in the field. In a similar vein, Women in Machine Learning (WiML) is a group of female data scientists and machine learning enthusiasts that provides support to this community.
Other initiatives include scholarships and training courses tailored especially for women in data science. For instance, the Anita Borg Institute helps women seeking degrees in computing and technology by providing scholarships and other forms of assistance.
Diversification in materials discipline will require concerted efforts from individuals, organizations, and assiduity. We can help ensure that data science benefits from the full range of talent and perspectives if we break down the barriers that prevent women from entering and succeeding in the field.
Recognizing the Impact of the Most Famous Women in Data Science
Despite the underrepresentation of women in data science, there have been multiple important female figures who made a significant impact on the industry, the world, and our (day-to-day) lives. It’s important to properly recognize and celebrate the accomplishments of those who have paved the path for other women to follow. Although data science may appear to be a somewhat new term, its history goes back to the early 1960s, the Second World War, and even to the period of Queen Victoria.
Image Description: Computer scientist Margaret Hamilton poses with the Apollo guidance software she and her team developed at MIT. Credit: Courtesy MIT Museum
Some of Margaret Hamilton’s most notable work was her contributions to the Semi-Automatic Ground Environment (SAGE) project and the Apollo missions. She worked on the SAGE project at MIT in the 1960s, where she wrote software to identify enemy aircraft.
In the late 1960s and early 1970s, she helped with coding the guidance and control systems of the Apollo mission at NASA, which is where she coded the term “software engineering” to describe the work she and her team were doing.
She received the Exceptional Space Act Award from NASA in 2003, and in 2016, she was presented with the Presidential Medal of Freedom by President Barack Obama.
2. Katherine Johnson
Image Description: Portrait of Katherine Johnson. Credits: NASA
Another influential female data scientist from the 1960s is Katherine Johnson, whose most notable contributions include data analysis for the United States Freedom 7 mission and calculations for the Friendship 7 mission.
She is credited with using data to calculate a perfect orbital trajectory path for Freedom 7. She also contributed to the mission that sent the first aircraft to orbit Earth and the Apollo 11 mission which sent the first man to the Moon.
Before her work at NASA, she already was paving the way for underrepresented groups, as she was one of the first three Black students to enrol in an integrated graduate program at West Virginia University.
Her contributions were also recognized by President Barack Obama with the Presidential Medal of Freedom in 2015.
3. Florence Nightingale
Image Description: Florence Nightingale portrait. Credits: Perry Pictures/Library of Congress, Washington, D.C. (LC-USZ62-5877)
Florence Nightingale, the founder of modern nursing, was also a data scientist. She recognized the importance of good record-keeping in hospitals and organized a Royal Commission, with the support of Queen Victoria, to analyze army mortality data.
Their analysis helped determine that the majority of soldier deaths were caused by preventable diseases. Making her impact even greater, Nightingale created a diagram, now known as the “Nightingale Rose Diagram”, to present the data demonstrating the decrease in death rates after implementing practices of the Sanitation Commission. Presenting the data accessibly helped advocate for new standards of sanitation.
4. Fei-Fei Lee
Image Description: Portrait of Dr Fei-Fei Lee in front of a whiteboard. Credits: Philip Montgomery
Dr Fei-Fei Li is a prominent American computer scientist who has made significant contributions to the field of artificial intelligence.
Her notable work includes serving as the chief scientist of AI at Google in 2017, being the inventor of ImageNet and the ImageNet Challenge, and being a leading advocate for advocating for diversity in STEM and AI.
She co-founded the non-profit organization AI4ALL, which focuses on promoting the diversity and accessibility of AI. Dr Li is widely regarded as an AI pioneer who places a strong emphasis on the importance of human values in the development of machine learning.
5. Dr Jeannette Wing
Image Description: Portrait of Dr Jeanette Wing. Credits: Microsoft
Dr Jeannette Wing, a computer science professor at Columbia's Data Science Institute, authored an essay in 2006 called "Computational Thinking," advocating for the importance of computational thinking as a valuable skill for everyone. She also held the position of Corporate Vice President of Microsoft Research, where she established a program to predict how technology would influence society within the next decade.
Dr Wing's contributions to computer science have earned her numerous awards, and she is a distinguished member of several esteemed organizations, such as the American Association for the Advancement of Science, the American Academy of Arts and Sciences, and the Institute of Electrical and Electronic Engineers (IEEE) as well as the Association for Computing Machinery (ACM).
6. Daphne Koller
Image Description: Portrait of Dr Daphne Koller. Credits: Pillar
Daphne Koller is a computer scientist and entrepreneur who has made significant contributions to the field of machine learning, particularly in the area of probabilistic models and Bayesian networks. She received her PhD from Stanford University in 1993 and went on to become a professor of computer science at Stanford, where she co-taught the university's first online course in 2011, which attracted over 100,000 students.
She has founded several successful startups in the field of artificial intelligence and machine learning, including Insitro, a company that uses machine learning to develop new drugs and therapies. She has received many awards for her work in the field of computer science.
The National Academy of Engineering, the American Academy of Arts and Sciences, and the International Society for Computational Biology are some of the prestigious organizations that Koller is a member of. She is a leading voice in the field of machine learning and one of today’s most influential women in technology.
Women and Code Labs Academy
Women in tech as well as in data science have been historically underrepresented however, there are outstanding examples of female data scientists over the years. We at Code Labs Academy believe that education should be available to everyone, among others, especially to women.
In our online event series “Women in Tech” we hosted in 2022, we aimed to give women a platform to share their experience within the industry. In addition, one of our corporate principles is diversity and inclusion, which is also reflected in the gender ratio of our team members: Currently, 52% of our company is female and 4% is non-binary. We want to ensure that we provide equal access to education for male, female, queer, and non-binary individuals.
In addition to our classroom courses in Berlin, we also offer online programming courses in Cyber Security, Data Science, UX/UI Design and Web Development. So anyone around the globe, no matter what gender, background, etc., can pursue their goal and start their first job in tech.
Learn More
If you’d like to learn more about our bootcamps or if you have any questions regarding our principles or values, reach out to us via email or give us a call.
Keep an eye out on Eventbrite for our workshops and events in-person in Berlin as well as completely remote events.
If you’d like to learn how to code, be assured, you’ll get the same chance as anyone else, when you study with Code Labs Academy.
Sources:
- https://www.collibra.com/us/en/blog/celebrating-four-female-data-scientists-who-changed-the-world#:~:text=Katherine%20Johnson%20is%20one%20of,female%20data%20scientists%20to%20date.
- https://odetta.ai/blogs/5-female-data-scientists-that-are-paving-the-way-in-2022-1
- https://www.analyticsvidhya.com/blog/2022/03/women-leaders-in-data-science-top-influentials-from-the-industry/
- https://profiles.stanford.edu/fei-fei-li
- https://www.history.com/topics/womens-history/florence-nightingale-1
- https://www.nasa.gov/content/katherine-johnson-biography
- https://www.britannica.com/biography/Margaret-Hamilton-American-computer-scientist
