Data scientists are crucial in companies after artificial intelligence (AI) boomed the internet world. One of the fastest-growing professions in the United States, the data scientist role is expected to surge 36% between 2021 and 2031.
While many academic individuals are looking forward to enrolling in a data science course, certain scientists are already excelling.
This article provides a brief overview of the top data science scientists and experts around the world.
Who Is a Data Scientist?
A data scientist is an individual who uses analytical and statistical data to explain and understand phenomena around the world and help companies make business decisions.
A data scientist can have classified tasks:
- Looking for patterns and trends in the dataset
- Creating algorithms and data models to forecast results
- Machine learning techniques to improve data quality
- Driving the company to the forefront of data innovations
- Utilizing data tools like SQL, Python, R, and SAS.
10 Most Influential Data Scientists in 2024
1. Andrew Yan-Tak NG
LinkedIn: Andrew NG
Andrew Yan-Tak NG is a British American computer scientist and technological entrepreneur who primarily works in machine learning (ML) and AI.
He is one of the Co-founders of Google Brain and a Former Chief Scientist at Baidu.
Andrew serves as a chair on the board of Woebot Labs, a provider of cognitive behavioural therapy. Currently, he is the founder of Deeplearning.AI and Managing. AI.
2. Alex Sandy Pentland
LinkedIn: Alex ‘Sandy’ Pentland
Named on Tim O’Reilly’s ‘The World’s 7 Most Powerful Data Scientists’ on Forbes in 2011, Alex Sandy Pentland is an American computer scientist, serial entrepreneur, and HAI fellow.
His research focuses on next-generation web infrastructure, AI, computational data science, and privacy. His two publications, Honest Signals (2010) and Social Physics (2015) won the Harvard Physics Business Review, respectively.
3. Randy Lao
LinkedIn: Randy Lao
Known as one of the aspiring data scientists in 2024, Randy Lao serves as a data mentor at Data Science Dream Job, an e-learning platform that focuses on the growth of data scientists. Presently, he is an affiliate marketing manager at Coursera. He also runs a site called CloudML, a free data science and machine learning source.
4. Larry Page
LinkedIn: Larry Page
Lawrence Edward Page, an American businessman, computer scientist, and internet entrepreneur primarily known for being the co-founder of Google, contributed to data science when it was not even a thing. In 2011, an Irish American author and publisher, Tim O’Reilly, named Larry Page one of the world’s most powerful data scientists.
5. Kyle McKiou
LinkedIn: Kyle McKiou
Kyle McKiou, an active contributor to LinkedIn, is the founder of Data Science Dream Job, a platform that teaches the subject from different backgrounds. Before he found the Data Science Dream Job, he was the senior director of data science at “The Marketing Store” in North America. He has also worked as a lead data scientist at the Anheuser-Busch InBev.
6. Geoffrey Hinton
Twitter: Geoffrey Hinton
Geffrey Hinton is a British-Canadian computer scientist and cognitive psychologist known for his contributions to artificial neural networks. In 2019, Hinton, along with Yoshua Bengio and Yann Le Cunn, received the Turing Award, also known as the Nobel Prize for Computing. The trio, Geoffrey Hinton, Yoshua Bengio, and Yann Le Cunn, were also referred to as the Godfathers of Deep Learning.
7. Andriy Burkov
LinkedIn: Andriy Burkov
Andriy Burkov is a data scientist and machine team leader at Gartner. He gained prominence with his authored piece, The Hundred Piece Machine Learning Book. With more than 100,000 copies sold, the books were published in different languages for global audiences.
8. Andreas Kretz
LinkedIn: Andreas Kretz
Andreas Kretz is a data scientist, engineer, and founder of Learn Data Engineering Academy. With more than two years of specialized coaching experience, he is known for helping more than 2,000 students who have reached goals in the essential field.
According to his LinkedIn profile, his achievements include, “8+ years of experience in Corporate Data Science, 14+ years in Computer Science and IoT, and a robust background as a Data Engineering and Data Labs Team Lead. His journey in Data Engineering has garnered global recognition, including being named a LinkedIn Top Voice in Data Science & Analytics in 2018, 2019, and 2024.
9. Dean Abbott
LinkedIn: Dean Abbott
A seasoned data science professional, Dean is the founder and Chief Executive Officer at Abbott Analytics. He has over 21 years of experience in data modelling, survey analysis, signal processes, and missile guidance.
Dean has authored Applied Predictive Analytics (Wiley, 2014, 2nd edition forthcoming) and is co-author of The IBM SPSS Modeller Cookbook (Packt Publishing, 2013).
10. Kirill Eremenko
LinkedIn: Kirill Eremenko
An alumni of The University of Queensland, Kirill Eremenko is the Founder and Chief Executive Officer of Super Data Science, an educational portal for aspiring data scientists. With his company’s mission as “Make The Complex Simple”, Super Data Science educates readers on complex topics like R Programming, Python, and Tableau to over-arching courses like Machine Learning A and Intro to Data Science.
Essential Skills Required To Become a Data Scientist
To embark on your career as a data scientist, here are some of the important skills.
1. Programming
Programming languages such as Python, R, SAS, and SQL are necessary to sort and analyze large amounts of data.
2. Statistics and Probability
Statistics and probability help create high-quality machine-learning models.
3. Data Wrangling and Database Management
Clean and organize complex data sets using data wrangling tools:
- Altair Monarch
- Talend
- Alteryx APA
- Trifacta
- Tamr
4. Machine Learning
Machine learning techniques like Linear Regression, Logistic Regression, Naive Bayes, Decision Tree, Random Forest Algorithm, and K-nearest Neighbour (KNN) are integral for analytical and statistical studies.
5. Data Visualization
Besides machine learning, an individual should be aware of analyzing, organizing, and computing data.
6. Cloud Computing
Cloud computing tools, such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud, are crucial for data science.
7. Interpersonal Skills
Along with technical skills, workplace skills like communication are important for team members in a technical organization.
Wrapping Up
From one theory to another, these acclaimed data scientists have made contributions that describe and ease the complexities of data science. Understanding the above-mentioned data scientists and their work adds depth to facts and topics ranging from machine learning to artificial intelligence.
