In the burgeoning realm of data science, the advent of 2024 heralds a pivotal moment as we cast our spotlight on a select cohort of luminaries driving innovation and shaping the future of analytics. The ‘Top 12 Data Science Leaders List’ serves as a beacon, celebrating these individuals’ exceptional expertise, visionary leadership, and substantial contributions within the field. Join us on this exploration of groundbreaking minds, as we navigate through their narratives, projects, and visionary outlooks that promise to shape the trajectory of data science. These exemplary leaders are not just pioneers; they embody the vanguards steering us into an era of unparalleled innovation and discovery.
Top 12 Data Science Leaders List to Watch in 2024
As we edge closer to 2024, we focus on a distinctive group of individuals showcasing remarkable expertise, leadership, and noteworthy contributions within data science. The “Top 12 Data Science Leaders List” aims to acknowledge and spotlight these individuals, recognizing them as thought leaders, innovators, and influencers anticipated to achieve significant milestones in the coming year.
As we delve deeper into the details, it becomes evident that these individuals’ viewpoints, undertakings, and initiatives can transform our methods and data utilization in addressing complex challenges spanning various sectors. 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 2024.
1. Anndrew 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. Anndrew Ng is a British-American computer scientist with Machine Learning (ML) and Artificial Intelligence (AI) expertise. Talking about his contribution to the development of AI, He is the Founder of DeepLearning.AI, the Founder & CEO of Landing AI, a General Partner at AI Fund, and an Adjunct Professor at Stanford University’s Computer Science Department. Moreover, he was the founding lead of the deep learning artificial intelligence research team under the Google AI umbrella- Google Brain. 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.
Mr. Anndrew Ng led the development of MOOC (Massive Open Online Courses) at Stanford University. He also founded Coursera and offered Machine Learning (ML) courses to over 100,000 students. 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, and he got the badge of Tiime’s 100 list of the most influential persons in the world.
“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 of artificial intelligence and Autopilot Vision at Tesla. Karpathy is passionate about deep neural nets. He started his journey from Toronto with a double major in Computer Science and Physics, and after that, he went to Columbia for further studies. There, he worked with Michiel van de Panne on learning controllers for physically simulated figures.
Moreover, he also worked with Fei-Fei Li for 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 and their intersection. He designed and was the first primary instructor for CS 231n: Convolutional Neural Networks for Visual Recognition. He is an enthusiastic blogger and developer of deep learning libraries and a passionate Data Science expert.
Amena Anadkumar is a Mysore, India-born, Bren professor at Caltech and serves as a senior director of AI Research at NVIDIA. She is an influencer with 159,417 followers, and her research interests are in large-scale machine learning, non-convex optimization, and high-dimensional statistics. Anadkumar holds degrees from the Indian Institute of Technology (IIT) Madras and Cornell University and was previously a principal scientist at Amazon Web Services. She is a fellow of ACM, IEEE, and the Alfred P. Solan Foundation. Her work in developing novel artificial intelligence accelerates AI’s scientific applications, including scientific simulations, weather forecasting, and drug design. She was awarded at NeurIPS and the ACM Gordon Bell Special Prize for HPC-Based COVID-19 Research.
“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 at Stanford Institute for Human-Centered Artificial Intelligence (AI) and Vision & Learning Lab. She is the inaugural Sequoia professor in the computer science department at Stanford University. She also worked as Vice President at Google and Chief Scientist of AI/ML at Google Cloud. With her years of expertise, she has worked closely in areas such as cognitively inspired AI, deep learning, machine learning, computer vision, AI in healthcare, and more.
Talking about her research, she has published 200+ scientific articles in conferences and significant journals of the relevant fields. ImageNet, developed by Fei-Fei Li, is a revolutionary project in the latest frontiers of Artificial Intelligence and deep learning. Along with the technical journey, she is the flag bearer at the national level for diversity in AI and STEM. She has received 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.
“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 known globally for his mobile robotics, machine learning, computer vision, and computational neuroscience work. LeCun founded convolutional nets and contributed to OCR and computer vision projects using convolutional neural networks. He is the founding director of the NYU Center of Data Science and was head of the image processing research department. Mr LeCun is one of the primary creators of DjVu and received the Turing Award in 2018 from Yoshua Bengio and Geoffrey Hinton for their contribution to deep learning.
LeCun is known for his contributions to machine learning, notably his 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.
“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, an American Computer Scientist, is well 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 holds 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. Talking about his prior work, Ian Goodfellow, with years of experience in deep learning, worked as a research scientist at Google Brain. After that, he joined Open AI (in their initial years) and then returned to Google research.
Ian Goodfellow has also researched and written the textbook “Deep Learning,” gained prominence for inventing generative adversarial networks. While at Google, he created a system facilitating the automatic transcription of addresses from Street View car photos for Google Maps. Additionally, Goodfellow exposed vulnerabilities in machine learning systems. In 2017, the MIT Technology Review recognized him among the 35 Innovators Under 35, and in 2019, Foreign Policy included him in the list of 100 Global Thinkers.
With 127,491 followers on LinkedIn, he is one of the data science leaders you can follow. Clement Delangue is the CEO and Co-founder at the Hugging Face. It is an open-source machine learning platform where researchers worldwide can share their AI models, datasets, and best practices. Talking about his academic background, he completed his Introduction to Computer Science and Programming Methodology at Stanford University. His first startup experience was with Moodstocks, for building machine learning for computer vision, and later it was acquired by Google. Before that, he was Co-Founder & CEO of VideoNot.es, a leading note-taking platform for the digital age. Then, he built a marketing and growth department for Mention – a leading European startup in 2014. With his expertise in Machine Learning, Hugging Face raised $160 M from Sequoia, Coatue, Lee Fixel, Lux, Betaworks, the first investors at Instagram & Snapchat, the chief scientist at Salesforce, and Kevin Durant.
With years of experience and research interest in Machine Learning, Natural Language Processing, Artificial Intelligence, and Software, Jay Alammar is the Director and engineering Fellow (Natural Language Processing) at Cohere. He started as a Partner in Machine Learning Engineering and Helps developers solve business problems with cutting-edge Language AI & NLP models. Now, he advises enterprises and developers on using large language models to solve real-world language processing use cases. He holds a Stanford degree in executive education, influence, and negotiation strategies program. Jay also has an English tech blog website for Machine Learning R&D, where he publishes all about NLP, machine learning, and artificial intelligence. Jay assisted 10,000+ learners on complex machine-learning topics. So, if you are looking for one of the best data science leaders, you can count on Jay Alammar.
“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 Partner of Apollo Projects. He previously worked at OpenAI as a Co-Founder and CEO. Sam Altman attended Stanford University but dropped out without earning a bachelor’s degree. He is one of the data science leaders known for Loopt, Y Combinator, and OpenAI. 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 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.
“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 2018 A.M. Turing Award alongside Geoffrey Hinton and Yann LeCun. Serving as a Full Professor at Université de Montréal, he founded and led Mila – Quebec AI Institute. Bengio is a Senior Fellow in the CIFAR Learning in Machines & Brains program and Scientific Director of IVADO. Notably, he received the Killam Prize in 2019 and, in 2022, achieved the status of the world’s most-cited computer scientist. Bengio is actively involved in addressing the societal impact of AI. He also contributed to the Montreal Declaration for Responsible Development of Artificial Intelligence.
“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 one of the Australian data scientist leaders, entrepreneurs, and educators. Howard commenced his career in management consulting at McKinsey & Co and AT Kearney, spending eight years before venturing into entrepreneurship. He 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 Perl’s evolution. Howard founded successful startups in Australia: email provider FastMail (acquired by Opera Software) and insurance pricing optimization company Optimal Decisions Group (ODG, developed by ChoicePoint). FastMail was among the pioneers in enabling users to integrate their desktop clients. He was the founding CEO of Enlitic, past president of Kaggle, Co-founder of Masks4All, Distinguished Research Scientist at the University of San Francisco, and founder of FastMail.FM and Optimal Decisions; ex-management consultant.
“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 and leading artificial intelligence (AI) figure, is renowned for his groundbreaking contributions to the field. 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’s 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.
In 2024, staying at the forefront of innovation in data science is crucial, and the top 12 are the trailblazers to follow. These 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.
