Fourteen inspiring and influential women who defy the gender gap in Data Science!

Just 15% of today's scientists are women. Like most STEM fields, data science has a daunting gender diversity problem. We need to do something about it.

Last week, I was having a "career conversation" with my 13 years old daughter; surprisingly, she has shown me a great interest in Artificial Intelligence and Data. I would not define her as a nerd, but she always got excellent grades in STEM.

As a father, I always try to encourage her, mentor her, and support her in the long way to come when it comes to her career and her decision, so I will do what it takes to give her all the possible opportunities to do her experiments until she finds out what it does for her in the life… but I must confess… We must do many things today to support female students' career choices.

There needs to be more diversity: as few as 15% of data scientists today are women. And the lack of diversity is a serious issue. A.I. algorithms are biased, so building them requires a team with a wide range of views and experiences.

Diversity of approaches and viewpoints is critical in building efficient data science teams. For example, machine learning algorithms occasionally "see" patterns that lead to spurious, biased, or even dangerous conclusions. A diverse group must ensure that bias-prone models produce accurate, balanced results. Building such algorithms can be an art as science.

But as explained by one study by BCG — Boston Consulting Group, data science, like most STEM fields, has a daunting problem of gender diversity.

While women make up about 55% of university graduates across countries on average, they account for just over one-third of STEM degrees. (See Exhibit 1.) Only two-thirds of this valuable talent pool embark on a STEM-related career, such as engineering, analytics, and software development, and even less on a data science career. According to different surveys, only about 15% to 22% of all data science professionals are women.

Also, While data scientist is the most promising job for the next years, according to Harnham's Diversity Report 2020–2021, females occupy only 18% of today's data science roles, and 11% of data teams don't have any women at all.

A career disconnection

According to Girls Who Code, during the last 30 years, female computer science graduates dropped from 37% to 18%. Girls'In addition, girls and STEM-related career paths disconnect before college. 74% of middle school girls are interested in STEM topics and careers, but only 0.4% of high school girls choose computer science as a major in college.

Girls who Code presents a few reasons why this is the case:

Inherent Bias: The narrative usually defines a "techie" individual as a geeky computer-tinkering male. This idea influences girls to turn away from computer science as an option for future studies.

No Early Exposure: A proper introduction to computing skills, such as coding or programming, at an early stage can cause a disconnection between the initial interest in STEM-related topics and the choice of other career paths.

Confidence Issues: When girls do not have confidence in their skills and potential success, they limit themselves. Internalized stereotypes can force women to feel they don't have the "right" knowledge or skillset for success in the field.

We need more women in Data Science.

Women are more aware of the risks that are a plus in big data. Women tend to excel in communication, team nurturing, and problem-solving. They have the natural talent for asking the right questions and listening to all the answers in the data.

Gender diversity can appeal to new customer bases, opening up untapped business opportunities for companies.

The concept of a data science team is relatively new, so companies must hire leaders who can work horizontally and listen to new ideas.

However, closing the technology gender gap should not only be about reaching a certain women-to-men ratio within the field. While recruitment remains an issue, the focus should be on empowering women in the area, recognizing their achievements, and reminding girls and women interested in or entering the field that skills are not gender-based.

Unfortunately, the gender gap in technology and data science remains, but bringing more women in isn't necessarily a push. Instead, it's a movement to raise awareness of the current situation, highlight growth opportunities, and highlight the benefits of gender diversity.

Women bring much, as they always have, to the technology table. But the support and recognition for what they get will continue to close the gender gap at a slow, steady pace…

An inspiring list of women in Data Science

As we saw, women are underrepresented in STEM science, technology, engineering, and math fields. However, being a father of three amazing daughters and having built my career in the tech industry, I will keep doing my best to support increasing the number of women in Tech, particularly in Data Science.

During my conversations with my daughter, I've started mentioning some inspiring women I've been following on the internet due to their exciting contributions to the community and inspiring careers.

Here you have an inspiring list of women's Tech profiles that can inspire many other women to pursue a career in A.I., Analytics, Big Data, Data Science, Machine Learning, and Robotics.

Fei-Fei Li

Associate Professor at the C.S. Dept. at Stanford, Director of the Stanford Artificial Intelligence Lab and the Stanford Vision Lab.

Dr. Fei-Fei Li is the inaugural Sequoia Professor in the Computer Science Department at Stanford University and was the Director of Stanford's A.I. Lab from 2013 to 2018.

Dr. Fei-Fei Li is the inventor of ImageNet and the ImageNet Challenge, a critical large-scale dataset and benchmarking effort. Dr. Li is also the author of more than 200 scientific articles in top-tier journals and conferences, with technical contributions as a leading national voice advocating diversity in STEM and A.I.

Dr. Li is co-founder and chairperson of the national non-profit AI4ALL to increase inclusion and diversity in A.I. education.

During her sabbatical, Dr. Li was Vice President at Google and Chief Scientist of AI/ML at Google Cloud.

She works with the world's most brilliant students and colleagues to develop smart algorithms that allow computers and robots to see and think and perform cognitive and neuroimaging experiments to discover how brains see and think.

LinkedIn: https://www.linkedin.com/in/fei-fei-li-4541247/

Twitter: Fei-Fei Li

Follow her on Medium: Fei-Fei Li

Cassie Kozyrkov

Chief Decision Scientist at Google, Inc.

Cassie is Google's data scientist and pioneer in democratizing decision intelligence and secure, useful AI.

Cassie was born in Saint Petersburg, Russia, in Port Elizabeth, South Africa. She studied economics and mathematical statistics at Nelson Mandela University. Kozyrkov worked as a PM and researcher at the University of Chicago. In 2016, she was promoted to Chief Data Scientist in the Office of the CTO at Google and later to Chief Decision Scientist in 2017. She focuses on Google's applied A.I. and data science process architecture. She has been a keynote speaker at Web Summit, the world's largest technology event. She appeared on the Forbes AI data science issue cover and was named the LinkedIn #1 Top Voice in Data Science and Analytics in 2019.

Twitter: @quaesita

Follow her on Medium: Cassie Kozyrkov

LinkedIn: https://www.linkedin.com/in/cassie-kozyrkov-9531919/

Allie Miller

US Head of A.I. Business Development, Startups, and Venture Capital at AWS, Forbes AI Innovator of the Year. Allie Miller is Amazon's U.S. Head of AI Market Growth for Startups and Venture Capital (AWS), advancing the world's largest A.I. firms. Previously, Allie was IBM's youngest woman to create an artificial intelligence device — spearheading large-scale product creation through computer vision, conversation, data, and regulation. Additionally, she was IBM's youngest woman to create an artificial intelligence product. Forbes named Allie and A.I. Summit as 2019's "A.I. Innovator of the Year" Allie is also the founder of The A.I. Pipeline to create more significant equity in ML, a national ambassador at the American Association for the Advancement of Science (AAAS), and an ambassador to 10,000-person Advancing Women in the Product organization. In three national innovation contests, she won the Grand Prize and spoke about A.I. worldwide. She holds the Wharton School double-major MBA and Dartmouth College B.A. in Cognitive Science …

Twitter: https://twitter.com/alliekmiller

LinkedIn: https://www.linkedin.com/in/alliekmiller/

Follow her on Medium: Allie Miller

Elizabeth M. Adams

Keynote Speaker | U.N. Key Constituent of Roundtable 3C on Artificial Intelligence| Stanford University Fellow: Race & Technology | Civic Tech

Elizabeth Adams is a technology integrator at the intersection of Cyber Security, A.I. Ethics, and A.I. Governance. She also passionately teaches, gives bits of advice, consults, speaks, and writes on the critical subjects of Diversity & Inclusion in Artificial Intelligence. She is a member of the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems, helping to build global standards for A.I. Nudging & Emotion A.I., and an appointed member of a Racial Equity Community Advisory Committee for the City of Minneapolis. In addition, she's refined her leadership acumen in tech design by leading various technology initiatives in the Washington D.C. metro area.

She has refined her leadership acumen in tech design over the past 20 years by heading numerous technology projects in the Washington D.C. Tube region. Returning to her home state of Minnesota, she remains committed to embedding ethics and human-centeredness into artificial intelligence systems and still takes time to fulfill her passion for lifting other women in Tech.

LinkedIn: https://www.linkedin.com/in/lizadams/

Tamara McCleary

CEO at Thulium Tamara McCleary is the CEO of Thulium.

She harnesses artificial intelligence, machine learning, data, and analytics to drive smart social in the B2B and enterprise.

She has been featured multiple times in Forbes for her pioneering influencer marketing strategies on social media.

She is a technology futurist, host of podcasts, TechUnknown and SAP Industries Live, keynote speaker, and unique advisor to leading tech companies.

LinkedIn: https://www.linkedin.com/in/tamaramccleary/

Twitter: @TamaraMcCleary

Carla Gentry

Data Scientist Carla was daunted to be a single mother with two sons but never backed a challenge.

Eager to learn and develop, she joined Chattanooga's Tennessee University in 1993. She worked for UTC in the Developmental Math Lab, helping students in all stages of mathematics.

After graduating from UTC with a dual major, Applied Mathematics and Economics, in 1998, she moved to Chicago to begin her analytics career.

Carla has over 19 years of experience working with several Fortune 100 and 500 businesses.

She is a liaison between the I.T. department and executive staff, taking complex databases, deciphering market needs, and returning with intelligence that quantifies investment, benefits, and patterns.

LinkedIn: https://www.linkedin.com/in/datanerd13

Twitter: @data_nerd

Follow her on Medium: Carla Gentry

Danielle Belgrave

Principal Researcher at Microsoft Research.

Danielle Belgrave is Principal Research Manager at Microsoft. She works on integrating expert scientific knowledge to develop probabilistic machine-learning models. Most of her work has focused on developing models to understand disease heterogeneity in asthma.

LinkedIn: https://www.linkedin.com/in/danielle-belgrave-704157107/

Twitter: https://twitter.com/DaniCMBelg

Kristen Kehrer

Machine Learning Storyteller, Founder of Data Moves Me, and Data Science Instructor at UC Berkeley Extension # 8 Global 2018 LinkedIn Top Voice — Data Science & Analytics. Kristen is a Data Science teacher at UC Berkeley Extension, Faculty / SME at Emeritus Management Institute, and Data Moves Me Founder, LLC. Kristen has provided creative and actionable machine learning solutions across various sectors, including infrastructure, healthcare, and eCommerce, since 2010. Kristen holds an M.S. at Worcester Polytechnic Institute in Applied Statistics and a B.S. in Mathematics.

LinkedIn:

Twitter: @DataMovesHer

Joy Buolamwini

Algorithmic Bias Researcher | Poet of Code |

Joy Buolamwini uses art and research to illuminate the social implications of artificial intelligence. She founded the Algorithmic Justice League to create a world with more equitable and accountable technology. Fortune Magazine named her to their 2019 list of the world's most outstanding leaders, describing her as "the conscience of the A.I. Revolution" She serves on the Global Tech Panel convened by the vice president of the European Commission to advise world leaders and technology executives on ways to reduce the harms of A.A. technology. In late 2018 in partnership with the Georgetown Law Center on Privacy and Technology, Joy launched the Safe Face Pledge, the first agreement prohibiting the lethal application of facial analysis and recognition technology. She holds two master's degrees from Oxford University and MIT; and a bachelor's degree in Computer Science from Georgia Institute of Technology.

LinkedIn: https://www.linkedin.com/in/buolamwini/

Chip Huyen

Machine Learning Engineer and Open Source Lead at Snorkel AI Chip Huyen is a computer scientist and writer at a startup that focuses on the machine learning production pipeline in Silicon Valley.

She helped launch Coc — Vietnam's second most popular web browser with 20+ million monthly active users.

LinkedIn: https://www.linkedin.com/in/chiphuyen/

Twitter: @chipro

Follow her on Medium: Chip Huyen

Fay Cobb Payton

Program Director at National Science Foundation; (Full Tenured) Professor of I.T./Analytics; ACM Education Advisory Board

Fay researches health care, UX design, the bias in computing/I.T. participation, data management and analytics, social & digital inclusion, and others. Her specialties include Health Informatics, Bias in Tech, Social Media, Program Evaluation, Curricula Development, Health Disparities, STEM/ STEM (+Arts) & Workforce Development. She works with I.T. industry professionals interested in retaining, sustaining, and mentoring people of color in and to executive leadership roles. She has visited 30 U.S. higher education institutions and several in Ghana to shadow members of executive leadership teams. She was an American Council on Education Fellow, which involved my participation in an academic college review team.

LinkedIn: https://www.linkedin.com/in/cobbpayton/

Kate Crawford

Co-founder of A.I. Now Institute, Senior Principal Researcher MSR, and Distinguished Research Professor at NYU

Kate Crawford is a professor and leading researcher studying the social implications of data systems, machine learning, and artificial intelligence.

Also, she collaborates at the École Normale Supérieure in Paris, where she is the inaugural Visiting Chair for A.I. and Justice. At New York University, she co-founded the A.I. Now Institute.

She has advised policymakers in the White House, the Federal Trade Commission, the United Nations, and the City of New York. In addition, she co-founded the Fairness, Accountability, Transparency, and Ethics (FATE) group at Microsoft.

She collaborates with The New York Times, The Atlantic, The Wall Street Journal, and Harper's Magazine as a writer.

She also is a member of the World Economic Forum's A.I. and Robotics Future Council.

Twitter: KateCrawford

Dr. Renata Afi Rawlings-Goss

Executive Director of the South Big Data Innovation Hub | Author | Data Career Coach

Renata Rawlings-Goss is a biophysicist by training. She is the founding Executive Director of the South Big Data Innovation Hub, whose mission is to catalyze partnerships among universities, industry, and government around Big Data, Data Science, and the "Internet of Things" She was awarded the first cohort of AAAS Big Data Policy Fellows supporting congress and the federal government. She was instrumental in creating the National Data Science Organizers group (NDSO.io) and implementing the NSF's priority goal to increase the U.S. workforce in data science. She also serves as the President/ CEO of Good with Data, LLC, which runs The Data Career Academy. She pursues efforts to increase the participation of women and underrepresented minorities in STEAM (Science, Technology, Engineering, Art/Design, and Math)

LinkedIn: https://www.linkedin.com/in/afiimani/

Conclusion

As an Artificial Intelligence evangelist and a very data-oriented person, I will be thrilled if my daughter decides to pursue a career in data science, information technology, engineering, or something that might help minimize the gender gap.

Our interactions and the software experiments we do together will positively affect how she perceives and uses technology now and in the future.

It's also crucial for young girls like my daughters to be exposed to positive examples of women in Tech, showing them technology as something they can be users and designers or builders. So I point out these women to my daughter in our everyday lives, and these awesome women are some examples in this post.

Follow me on LinkedIn for more info: www.linkedin.com/jairribeiro

Other helpful resources

Below is a list of other prominent female data science and computing support resources.

The women in Data Science (WiDS) Conference aims to inspire and educate data scientists worldwide, regardless of gender. WiDS started as a one-day technical conference at Stanford in November 2015. Five years later, the WiDS is a global movement with several initiatives.

Harvard's Women in Computer Science (WiCS) Advocacy Council — A very active community of faculty and students at Harvard University aiming to understand and reduce the technology gender gap.

Girls Who Code — GWC is a non-profit organization that inspires high-school girls to pursue opportunities in the computing field.

National Center for Women & Information Technology (NCWIT) — A non-profit community of universities, companies, non-profits, and government organizations that aims to increase women's engagement in computing science and technology.

Women in Big Data Forum — This active LinkedIn forum promotes diversity in the big data industry through mentoring and peer participation.

Progressive Women's Leadership — A resource center that aims to foster women's leadership in the workplace.

Would you like to support me?

To access unlimited stories, consider signing up to become a Medium member for just $5. In addition, if you sign up using my link, I'll receive a small commission (at no extra cost).

Here are ten other Articles you surely want to read.

• Meta just released LLaMA: a Language Model that can Revolutionize Business Communication and Automation.
• Ten cool things you should know about ChatGPT
• Introducing ChatGPT to Your Team: A Guide to Winning Over the Big Boss
• The most impressive Youtube Channels for you to Learn AI, Machine Learning, and Data Science.
• This is how I'm using AI to answer great Philosophical Questions
• What is TinyML, and why does it matter?
• A quick look under the hood of Stable Diffusion Open Source architecture.
• These are some of the best Youtube channels where you can learn PowerBI and Data Analytics for free.
• The Relevancy of Analytics Insights to your company Today: A Practical Guide
• Becoming the Michael Jordan of Data Science: A Step-by-Step Guide

Follow me on LinkedIn for more info: www.linkedin.com/jairribeiro