Introduction

Data science has been a hot topic for a few years now, captivating the minds of techies and playing a significant role in the growth and development of businesses. As we step into the automation-centric future, the potential of data science is boundless, and the leaders in the field will be the torchbearers of future innovation. Join us as we cast a spotlight on some of the greatest leaders in data science, celebrating their exceptional expertise, visionary leadership, and substantial contributions within the field. This blog lists the top 12 data science leaders to follow for the latest updates and innovations in the field.

Top 12 Data Science Leaders to Watch in 2024

As we edge closer to 2024, here is a list of distinctive individuals who have showcased remarkable expertise, leadership, and noteworthy contributions in the field of data science. This list aims to acknowledge these individuals as data science leaders to follow in 2024.

Whether it entails progress in predictive analytics, advocacy for ethical AI practices, or developing cutting-edge algorithms, the individuals highlighted in this list are poised to influence the terrain of data science in the coming year.

Andrew Ng

“A lot of the game of AI today is finding the appropriate business context to fit it in. I love technology. It opens up lots of opportunities. But in the end, technology needs to be contextualized and fit into a business use case.”

Dr. Andrew Ng is a British-American computer scientist with Machine Learning (ML) and Artificial Intelligence (AI) expertise. He is the Founder of DeepLearning.AI, the Founder & CEO of Landing AI, a General Partner at the AI Fund, and an Adjunct Professor at Stanford University’s Computer Science Department. He also served as a Chief Scientist at Baidu, where he mentored a 1300-person AI group and developed the company’s AI global strategy. Moreover, he was the founding lead of Google Brain – the deep learning artificial intelligence research team under Google’s AI umbrella.

Andrew Ng is also actively involved in the field of education. He co-founded Coursera and offered Machine Learning (ML) courses to over 100,000 students. He also led the development of MOOC (Massive Open Online Courses) at Stanford University. Being a pioneer in ML and online education, he holds degrees from Carnegie Mellon University, MIT, and the University of California, Berkeley. Moreover, he co-authored over 200 research papers in ML, robotics, and related fields. Acknowledging all of his contributions to the field, Time Magazine listed him as one of the 100 most influential people in AI in 2023.

Website | Twitter

Andrej Karpathy

“We were supposed to make AI do all the work, and we play games, but we do all the work, and the AI is playing games!“

Andrej Karpathy, a Slovak-Canadian PhD holder from Stanford, is building a kind of JARVIS at OреոΑӏ. He was the Director of AI and Autopilot Vision at Tesla. Karpathy is most passionate about deep neural nets. He started his journey from Toronto with a double major in Computer Science and Physics, after which, he went to Columbia for further studies. There, he worked with Michiel van de Panne on learning controllers for physically simulated figures.

He also worked with Fei-Fei Li during his Ph.D. at Stanford Vision Lab, where he worked on the Convolutional Neural Network and Recurrent Neural Network architectures and their applications in Natural Language Processing and Computer Vision. He designed the course CS 231n: Convolutional Neural Networks for Visual Recognition and was its first primary instructor. Moreover, he is an enthusiastic blogger, a developer of deep learning libraries, and a passionate Data Science expert.

Website | Twitter

Amina Anandkumar

Amina Anandkumar is an India-born Bren professor at Caltech and serves as a Senior Director of AI Research at NVIDIA. She was previously a Principal Scientist at Amazon Web Services as well. Anandkumar holds degrees from the Indian Institute of Technology (IIT) Madras and Cornell University and is a fellow of ACM, IEEE, and the Alfred P. Solan Foundation.

She is an influencer with over 150k followers and shares updates on large-scale machine learning, non-convex optimization, and high-dimensional statistics. Her work in developing novel artificial intelligence has accelerated AI’s scientific applications, including scientific simulations, weather forecasting, and drug design. Her HPC-based COVID-19 Research was recognized at NeurIPS and was awarded the ACM Gordon Bell Special Prize.

Website | Twitter

Fei-Fei Li

“I believe in the future of AI changing the world. The question is, who is changing AI? It is really important to bring diverse groups of students and future leaders into the development of AI.” 

Fei-Fei Li is a Co-director of Human-Centered Artificial Intelligence and the Vision & Learning Lab at Stanford Institute. She is the inaugural Sequoia professor in their computer science department as well. She has also worked as Vice President at Google and Chief Scientist of AI/ML at Google Cloud. Over her years of experience, Li has worked in diverse areas ranging from cognitively inspired AI, and deep learning to machine learning, computer vision, and AI in healthcare.

Talking about her research, she has published over 200 scientific articles at conferences and significant journals in the relevant fields. ImageNet, developed by Fei-Fei Li, is a revolutionary project in the latest frontiers of artificial intelligence and deep learning.

She has received many awards for her work, including the ELLE Magazine’s 2017 Women in Tech, a Global Thinker of 2015 by Foreign Policy, and the prestigious “Great Immigrants: The Pride of America” by Carnegie Foundation in 2016. As an industry leader, she also stands as a flag bearer for diversity in AI and STEM at the national level.

Stanford Profile | Twitter

Yann LeCun

“AI is an amplifier of human intelligence & when people are smarter, better things happen: people are more productive, happier & the economy strives.”

With expertise in research, technical consulting, and scientific advising, Yann LeCun is the Chief AI Scientist at Facebook. He is the Founding Director of the NYU Center of Data Science and headed the Image Processing Research department. He is known globally for his work in mobile robotics, machine learning, computer vision, and computational neuroscience.

LeCun founded convolutional nets and contributed to OCR and computer vision projects using convolutional neural networks. These biologically inspired networks were applied to optical and handwriting recognition, creating a bank check recognition system. This system was adopted by NCR and other companies and processed 10% of all U.S. checks in the late 1990s and early 2000s.

LeCun is one of the primary creators of DjVu and received the Turing Award in 2018 along with Yoshua Bengio and Geoffrey Hinton for their contributions to deep learning.

Website | Twitter

Ian Goodfellow

“Even today’s networks, which we consider quite large from a computational systems point of view, are smaller than the nervous system of even relatively primitive vertebrate animals like frogs.”

Ian Goodfellow is an American computer scientist, best known for his research work in Machine Learning. He serves as a Director of Machine Learning at Apple. Under the supervision of Andrew Ng, he recieved a B.S. and M.S. in Computer Science from Stanford University. He also got a Ph.D. from Université de Montréal under the supervision of Yoshua Bengio and Aaron Courville.

Ian Goodfellow initially worked as a Research Scientist at Google Brain. After that, he joined Open AI in their initial years, and then returned to Google research. While at Google, he created a system facilitating the automatic transcription of addresses from Street View car photos for Google Maps. Additionally, he exposed vulnerabilities in machine learning systems.

Goodfellow has also researched and written the textbook “Deep Learning,” which gained prominence for inventing generative adversarial networks (GAN). In 2017, the MIT Technology Review recognized him among the 35 Innovators Under 35, and in 2019, Foreign Policy included him in their list of 100 Global Thinkers.

Website | Twitter

Clément Delangue

Clement Delangue is the CEO and Co-founder of Hugging Face, an open-source machine learning platform where researchers worldwide share their AI models, datasets, and best practices. With his expertise in Machine Learning, Hugging Face raised $160 M from Sequoia, Betaworks, Salesforce, Kevin Durant, and other industry leaders.

He started off as the Co-Founder & CEO of VideoNot.es, a leading note-taking platform for the digital age. He then built a marketing and growth department for Mention – a leading European startup in 2014. His first startup experience was with Moodstocks, where he worked on building machine learning models for computer vision, which was later acquired by Google.

Talking about his academic background, he studies “Introduction to Computer Science and Programming Methodology” at Stanford University. Now, with over 120k followers on LinkedIn, he is definitely a voice in data science worth listening to.

Twitter

Jay Alammar

With years of experience and research interest in ML, NLP, AI, and software, Jay Alammar is the Director and Engineering Fellow of Cohere. He started as a Partner in Machine Learning Engineering and helps developers solve business problems with cutting-edge AI & NLP models. Now, he advises enterprises and developers on using large language models to solve real-world language processing use cases.

Alammar holds a degree in “Executive Education, Influence, and Negotiation Strategies” from Stanford, and has gone on to assist over 10,000 learners on complex machine-learning topics. He also runs an English tech blog website for Machine Learning R&D, where he publishes all about NLP, ML, and AI. So, if you are looking for a data science leader to follow, Jay Alammar is one of your best bets.

Website | Twitter

Sam Altman

“AI will probably most likely lead to the end of the world, but in the meantime, there’ll be great companies.”

Sam Altman is a Co-founder of Apollo Projects and has been the CEO of OpenAI since 2019. He attended Stanford University but dropped out after two years. In 2005, at 19, Altman co-founded Loopt, a location-based social networking app, securing over $30 million in venture capital as CEO. Despite the acquisition by Green Dot for $43.4 million in 2012, Loopt struggled.

Altman then joined Y Combinator in 2011, becoming its president in 2014, overseeing a total valuation of $65 billion for companies like Airbnb and Dropbox. In 2016, he expanded his role to include YC Group. Altman initiated YC Continuity and YC Research, funding mature companies and a research lab. In 2019, he transitioned to Chairman at YC, later focusing on Tools For Humanity, a 2019 venture providing eye-scanning authentication and Worldcoin cryptocurrency for fraud prevention.

Website | Twitter

Yoshua Bengio

“AI will allow for much more personalized medicine.”

Renowned globally for his expertise in artificial intelligence, Yoshua Bengio is a trailblazer in deep learning, honored with the prestigious Turing Award in 2018, alongside Geoffrey Hinton and Yann LeCun. Bengio is a Senior Fellow in the CIFAR Learning in Machines & Brains program and the Scientific Director of IVADO. Serving as a Full Professor at Université de Montréal, he founded and led the Mila – Quebec AI Institute.

Notably, he received the Killam Prize in 2019 and, in 2022, achieved the status of the world’s most-cited computer scientist. Bengio, who is actively involved in addressing the societal impact of AI, has also contributed to the Montreal Declaration for Responsible Development of Artificial Intelligence.

Website | LinkedIn

Jeremy Howard

“Data science is not software engineering. There’s a lot of overlap…but what we’re doing right now is prototyping models.”

Jeremy Howard is an Australian data science leader, entrepreneur, and educator. He was the founding CEO of Enlitic, past president of Kaggle, Co-founder of Masks4All, Distinguished Research Scientist at the University of San Francisco. He commenced his career in management consulting at McKinsey & Co and AT Kearney, spending eight years before venturing into entrepreneurship.

Howard has also founded two successful startups: an email provider, FastMail (acquired by Opera Software), and an insurance pricing optimization company, Optimal Decisions Group (ODG, developed by ChoicePoint). FastMail was among the pioneers in enabling users to integrate their desktop clients.

Howard contributed notably to open-source projects, playing a key role in developing the Perl programming language, Cyrus IMAP server, and Postfix SMTP server. As the chair of the Perl6-data working group and author of RFCs, he significantly influenced the evolution of Perl.

Website | LinkedIn

Demis Hassabis

“I would actually be very pessimistic about the world if something like AI wasn’t coming down the road.“

Demis Hassabis is a British computer scientist, artificial intelligence researcher, and entrepreneur. He is a polymath, renowned for his groundbreaking contributions to the field of AI. Born in 1976, Hassabis displayed prodigious talent in chess, becoming a Grandmaster at just 13. Transitioning to academia, he pursued computer science at Cambridge.

Hassabis later co-founded the pioneering video game company Elixir Studios. In 2010, he founded DeepMind, an AI research lab acquired by Google in 2014. Hassabis’ work at DeepMind has led to significant advancements in machine learning, particularly in the realm of deep reinforcement learning. His endeavors underscore a commitment to pushing the boundaries of AI’s capabilities, making him an industry leader to look out for.

Website | Twitter

Conclusion

In 2024, staying at the forefront of innovation in data science is crucial, and the 12 leaders mentioned above are the trailblazers to follow. These industry leaders, pioneers in big data analytics, and experts in data science, continue to shape the landscape with their visionary insights and groundbreaking contributions. From navigating complex algorithms to leveraging the power of machine learning, these data science leaders are steering the course for the future. Following their guidance provides an unparalleled opportunity to stay abreast of the latest trends and advancements in data science, making them indispensable figures for anyone navigating the dynamic world of data analytics.