Top Women Opinion Leaders in Data Science - Changing the Game
Summary
Discover the inspiring rise of women in data science! Despite its historically male-dominated landscape, the field is witnessing a significant shift. Meet some remarkable female figures driving this change. With organizations and initiatives focused on women's empowerment, the future of data science isn't just diverse—it's inclusive and empowering for all.
Table of Content
Though, the data science field has traditionally been dominated by men, women are expanding their presence and influence in the field of data science.
Despite all the difficulties, a number of noteworthy female figures have achieved success in this profession and have emerged as role models for women in Data Science, Artificial Intelligence and Machine Learning.
This is giving other female data scientists a fantastic opportunity to put their analytical skills to use.
Additionally, there are now more organizations and initiatives dedicated to supporting and empowering women in data science, such as Women in Data, Women in Machine Learning (mentorship program), and the Women in Data Science (WiDS) conference.
Hence, OdinSchool did some research and picked up the top female influencers in data science.
Remarkable Women in the Data Science field
#1. Cassie Kozyrkov
One of the Top LinkedIn Voices
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Cassie Kozyrkov is the chief decision scientist at Google Cloud and a well-known speaker and writer on topics related to data science, machine learning, and artificial intelligence.
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Her mission is to democratize Decision Intelligence and safe, reliable AI.
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Cassie has provided guidance on more than 100 projects and designed Google's analytics program, personally training over 20,000 Googlers in statistics, decision-making, and machine learning to date.
Listen to Cassie’s views on Decision intelligence (ML++). You can catch her popular series Making Friends with Machine Learning here or dishing out her opinions and inspiring insights on Twitter or Medium.
Connect with Cassie Kozyrkov | Linkedin - 565,760 followers | Twitter - 45k followers | Medium - 174kfollowers |
#2. Fei-Fei Li
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One of the top minds in Data Science and Artificial Intelligence, Li is co-creator of ImageNet, a visual object recognition database which heralded the beginning of the deep learning revolution.
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She is cofounder of AI4ALL, a nonprofit dedicated to boosting diversity and inclusion in AI education, research, development and policy.edu. During a sabbatical as chief scientist for AI at Google Cloud, Li warned against the tech giant's A.I. contract with the Pentagon.
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She has authored more than 100 scientific articles and received numerous honors, including the IBM Faculty Fellow Award the Alfred Sloan Faculty and the 2009 NSF Career Award.
My students and I are passionate about AI research! We work on: machine learning, deep learning, computer vision, robotics, computational neuroscience, cognitive neuroscience, AI and healthcare.
Connect with Fei-Fei Li | Twitter - 451k followers | LinkedIn - 28,382 followers |
#3. Daliana Liu
One of the Top LinkedIn Voices
With over 250K LinkedIn followers, Daliana has become a household name in the data science world.
When she’s not busy at her job as senior data scientist at Predibase, an enterprise declarative machine learning platform, she hosts The Data Scientist Show and writes about how to grow a successful career in data science.
I'm from Dalian, a coastal city in China. I lived in LA and Seattle before I moved to SF. I just love the smell of the sea. (and the smell of coffee!)
Connect with Daliana Liu | LinkedIn - 265,444 followers | Twitter - 5852 followers | Medium - 1.7k followers | Newsletter |
#4. Megan Lieu
Megan is a data advocate at DeepNote.
She was a data scientist at Narrator and runs a LinkedIn Learning course on how to Choose the Right Tool for Your Data: Python, R, or SQL. She loves making sense of messy data and is building her career and skills in public, alongside her 100K+ LinkedIn followers.
I have vivid memories of the highs I would get from successfully solving practice problems in algebra and calculus classes in middle school and high school. That’s where it all started. From there, my love for numbers brought me to the world of transaction advisory and business valuations, where those numbers served as the foundation for complex financial models I built.
You can follow her programming, querying, data management and visualization journey on LinkedIn and get a scoop on data science on Medium.
Connect with Megan Lieu | LinkedIn - 102,284 followers | Twitter - 35 followers | Medium - 3 followers |
#5. Usha Rengaraju
Usha Rengaraju is the first woman developer of AI in India.
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She conducted India's first neuro-AI conference. As part of this initiative, she is currently working as the ambassador at AI Med (a group of enthusiasts, expert physicians and AI experts)
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She specializes in Probabilistic Graphical Models, Machine Learning and Deep Learning. She loves competitive Data Science and is also a Kaggle GrandMaster.
Listen to Usha’s views on Need for women in AI
Connect with Usha | Twitter - 2350 followers | LinkedIn - 33736 followers |
#6. Cindi Howson
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Cindy is a disruptor of all things data, BI and analytics, specializing in providing the right analytics for the right use case.
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The ThoughtSpot chief data strategy officer and host of The Data Chief Product podcast is a prolific influencer in the data world.
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With a career spanning over two decades, prior to ThoughtSpot, Cindy served as VP Data and Analytics at Gartner and founded BI Scorecard®.
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She is also the author of multiple books including Successful Business Intelligence: Unlock the Value of BI & Big Data and SAP BusinessObjectsBI 4.0: The Complete Reference.
Read Cindy’s interview on how she balances her personal and professional life with she reaching such great heights in her career .
Connect with Cindi Howson | Twitter - 25.7k followers | LinkedIn - 23263 folllowers |
#7. Anima Anandkumar
Her work developing novel artificial intelligence algorithms enables and accelerates scientific applications of AI, including scientific simulations, weather forecasting, autonomous drone flights, and drug design.
She has received best paper awards at venues such as NeurIPS and the ACM Gordon Bell Special Prize for HPC-Based COVID-19 Research and also a part of the World Economic Forum's Expert Network.
Connect with Anima Anandkumar | LinkedIn - 176163 followers | Twitter - 23.5k followers |
Final Thoughts
In essence, the rise of women in data science is not just a statistic but a testament to resilience, innovation, and empowerment.
As more women step into the spotlight, they're not only reshaping the field but also inspiring a new generation of data enthusiasts. Their stories remind us that determination knows no gender, and the future of data science is brighter and more inclusive than ever before.
Hence, we would say, there could not be a better time to pursue data science, especially with a comprehensive data science course with an industry-vetted curriculum.
Frequently Asked Questions About Women in Data Science
Q1: Can a woman pursue data science?
Absolutely! Data science is a field open to anyone with the interest, skills, and determination to excel in it, regardless of gender. Many women have made significant contributions to the field of data science, and there are numerous opportunities for women to pursue rewarding careers in this rapidly growing field.
Q2: I took a career break for 10 years for my family. Can I also become a data scientist?
Absolutely! Taking a career break for family reasons doesn't diminish your ability to pursue a career in data science. In fact, many individuals successfully transitioned, just like The Career Relaunch of A Full-Time Mother After A 6-Year Break
Q3: Why should a woman pursue data science?
Women should pursue data science because it offers great opportunities, is needed in many industries, provides good jobs, is fair for everyone, adds diversity, pays well, and helps you learn and grow. best example would be Kriti's Non-IT Journey in Data Science
There are so many data science courses out there. Which one should I consider?
Always look for the data science courses that cover foundational concepts. Check the curriculum, instructor credentials, and reviews to ensure the course matches your learning objectives and offers quality content like OdinSchool.