Top 5 Data Scientists
  • Introduction
  • Top 5 data scientists in the world in 2021
  • Geoffrey Hinton
  • DJ Patil
  • Jeff Hammerbacher
  • Fei-Fei Li
  • Dean Abbott
  • Takeaway



Data science has always been a revolutionary and dynamic field. In recent years, the rising importance of Machine Learning and Artificial Intelligence has transformed the meaning of technology related to data science. It is not surprising to see so much hype around these fields. Data scientists have consistently been featured within the list of top 5 experts, with innovations and discoveries originating from humans as we experience a transformation.

The world of data science is transforming. In order to keep up with the latest developments, it has become necessary for data experts to upgrade their skills on a regular basis. 

Few data scientists have earned fame for their immense knowledge of the subject, and they are helping to increase awareness about the evolution of data technology. We can learn a lot from their journey and experiences. These 5 data scientists have reached global acclaim for their innovative work.

A quick look at the top 5 data scientists in the world in 2021.


Geoffrey Hinton

Geoffrey Hinton is an expert in artificial intelligence and a pioneer in deep learning. He was one of the researchers who presented the backpropagation algorithm and used it for word embeddings. In his years of career, Hinton has invented several foundational deep learning techniques. His additional contributions to neural network research include Boltzmann machines, mixtures of experts, variational learning, distributed representations, time-delay neural nets, and deep learning. Hinton’s research group in Toronto made significant discoveries in deep learning that transformed object classification and speech recognition.

Geoffrey Hinton is a member of the UK Royal Society and a foreign part of the American Academy of Arts and Sciences and the National Academy of Engineering. Throughout the years, he was awarded several accolades, including:

  • The David E. Rumelhart Prize
  • The IJCAI Award for research excellence
  • The Killam Prize for Engineering
  • The IEEE Frank Rosenblatt medal, the NSERC Herzberg Gold Medal
  • The IEEE James Clerk Maxwell Gold Medal
  • The NEC C&C award
  • The BBVA award
  • The Honda Prize
  • The Turing Award


DJ Patil (Dhanurjay Patil)

The term “Data Scientist” was first coined by D.J. Patil and Jeff Hammerbacher and is often associated with the tagline “Data Science as the sexiest job of the 21st century!”

DJ Patil is the former US Chief Data Scientist (during the tenure of former US President Barack Obama), having held that position from October 2014 until January 2017. Prior to that, he was an entrepreneur and a venture capitalist for a decade in Silicon Valley and is currently the US State Department’s first Foggy Bottom Fellow (at Stanford University). 

DJ Patil played a notable role in converting the power of data for the benefit of citizens. He has been a leading consultant to many companies, including LinkedIn, Skype, Salesforce, PayPal, and Greylock Partners.

DJ Patil has also authored books- Ethics and Data Science, Building Data Science Teams, Data Jujitsu: The Art of Turning Data into Product and Data-Driven. For his active service in national security, Patil was awarded by Secretary Carter the Department of Defense Medal for Distinguished Public Service- the highest honour the department presents to a civilian.


Jeff Hammerbacher

Jeff Hammerbacher co-founded the term “Data Scientist” alongside DJ Patil. The New York Times famously featured him as “Dr Data.” He developed several methods and techniques to capture, analyse and store an enormous amount of data. He was bought-in from Wall Street to Facebook to solve Data Problems.

Jeff Hammerbacher is the former Chief Technology Officer of Cloudera, a tech company that develops commercial products based on open-source technology developed at Google. At present, he holds the position of Distinguished Engineer at Facebook since July 2014. Prior to this, he was a Research Director in Facebook’s data science team. He is also a speaker at the Conference on Knowledge Discovery and Data Mining, an ACM Distinguished Scientist, a board member of Quantopian, and an advisor in Cloudera.

Hammerbacher built an entirely new technology to handle Data Overload, which was Facebook’s top issue at the time. He created a new open-source database project called Hadoop, which allowed real-time processing of large quantities of data—which was never done before. He led and built Facebook’s Data team.

Hammerbacher was a former faculty member at the Icahn School of Medicine at Mount Sinai. He has also authored a book named “Beautiful Data: the stories behind elegant data solutions.”  


Fei-Fei Li

Fei-Fei Li is a top AI research scientist. She is the Director of the Stanford Artificial Intelligence Lab and Stanford Vision and Learning Lab, which includes more than 30 faculty members. She is a pioneer in computer vision, cognitive neuroscience, machine learning, artificial intelligence, and artificial intelligence for healthcare.

Li’s latest project involves trying to teach AI agents with virtual reality. The idea is to use VR as a way of teaching AI about the real world in case AI doesn’t turn out to be great at things like reading books and interpreting art. 

Fei-Fei Li’s lab focuses on applying cutting-edge deep learning technologies, creating new training methods, and fundamental principles of human vision and perception to build novel models for computer vision.

In 2017, Fei-Fei Li was appointed head of AI by Google Cloud and a member of the board of directors at Alphabet Inc., and an external adviser to DeepMind, owned by Alphabet. In addition, she is on the faculty as part of the Chinese University in Hong Kong.

Li has had a remarkable impact on the domain of artificial intelligence and is a member of the National Academy of Medicine, National Academy of Engineering, and American Academy of Arts and Sciences.

For her phenomenal work in Artificial Intelligence, WIRED has featured Li as a “researcher bringing humanity to AI.” Li is the inventor of ImageNet and the ImageNet Challenge, a critical large-scale dataset and benchmarking effort that has enriched deep learning and AI advancements. She is also Chair and Co-founder of a non-profit organisation called AI4ALL, aiming to amplify AI education diversity.

Li has authored and published over 200 scientific articles. She has also worked on Crowdsourcing in Computer Vision and Nanking 1937: Memory and Healing.

Few honourable mentions of Fei-Fei Li: 

  • 2019 IEEE PAMI Longuet-Higgins Prize
  • 2019 National Geographic Society Further Award
  • 2017 Athena Award for Academic Leadership
  • IAPR 2016 J.K. Aggarwal Prize
  • The 2016 IEEE PAMI Mark Everingham Award
  • The 2016 Nvidia Pioneer in AI Award


Dean Abbott

Dean Abbott is an experienced data analyst and data scientist with over 20 years in the field. He has an extensive academic resume, his work including research on computer vision, data analytics, and artificial intelligence.

Currently working as an author and consultant for Abbott Analytics, he also operates a personal blog dedicated to discussions on AI technology and its current limitations.

Abbott’s previous work includes numerous papers with high impact factors, including one from the prestigious Journal of Artificial Intelligence Research. While his research specialities include deep learning, natural language processing, and computer vision, he has applied statistical models to real-world problems in fields as diverse as pharmaceutical research and national security.

Abbott is Chief Data Scientist and Co-Founder at SmarterHQ, President of Abbott Analytics in California, and Co-Founder of SmarterRemarketer, a company that focuses on web analytics and data-driven marketing attribution.

Dean Abbott has authored the books- “Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst and IBM SPSS Modeler Cookbook.”



There are many data scientist experts that have made a significant contribution to the field of data science. This list evaluates people who have changed the course of Data Science and defined what it should be.

As an aspiring Data Scientist, you might take some references from their work.

Which Data Scientist inspired you to transform your career in Data Science? Let us know your inspirations and if you would like them to be featured here!