Data is the cornerstone of every technology around us. It drives our lives and is deeply ingrained in our digital culture. From booking a cab, ordering at restaurants, to making hotel reservations etc., our lives have become easier due to the advent of Big Data and Machine Learning.
However, all these innovations are made possible thanks to the masterminds who spearhead the field. Who are the ones moving the industry ahead and doing their best? It’s the top data science leader in the world.
2021 will be a pivotal year for data scientists as organizations are increasingly relying on insights derived from Big Data for making key decisions. More applications are being created with Python and there’s an increased demand for end-to-end AI solutions. There are a lot of jobs available in the field, however, not enough data scientists. According to an ASA Report, nearly 70% of business owners prefer job applicants with specializations in data science and the number of job openings are projected to grow to 2.72 million by 2021.
Aspiring data scientists often learn by visiting websites such as Coursera and Kaggle but one of the best ways to learn fast is by taking tips from the greats. If you’re new to the field of Data Science and want to truly excel, recognizing the people who are big influencers, authors, and evangelists of Machine Learning are important. Data Science is constantly evolving, which means you have to stay in touch with industry trends and translate business requirements into real-world solutions. Although there’s no roadmap to being a professional or expert in data science and every beginner’s journey is different, following these data science leaders is a good start.
Get ready to learn from their experiences and soak in technical knowledge that spans over decades. Who knows, maybe you’ll become the next big entrepreneur or start your own business after drawing inspiration from their stories. Let’s get to the list.
Data Science Leaders You Should Follow
1. Jose Marcial Portilla
Jose Marcial Portilla is one of the first names you’ll hear about in the data science community because of his Python for Machine Learning and Data Science Bootcamp. Most beginners get their strong foundations in the field by going through his course, and not just by reading textbooks, blogs, or watching videos online. What’s unique about Jose is that he’s generous with his technical expertise and doesn’t hesitate to showcase it. He is constantly learning and a great mentor to data science students, having released many Machine Learning courses which are easy to understand and walk you through the basics.
He is currently the Head of Data Science in Pierian Data Inc. and provides Fortune 500 Companies with data science and programming consultation services.
2. Koo Ping Shung
Koo Ping Shung is one of the co-founders of DataScience SG and a giant in the community. He had humble beginnings and shows up at science meetups in Singapore where he educates peers and fresh graduates on how to attain a strong foothold in their data science careers. He posts newsletters on Medium where you can find him talking about ethics in Artificial Intelligence, the best learning resources for Data Scientists, and how to develop business acumen while analyzing Big Data.
Koo Ping Shung can quickly come up with innovative data science strategies, solutions, and is a walking encyclopedia of Machine learning and AI information. You can find him posting various articles on his LinkedIn profile. He also managed the Earth Hour Project which was conducted in 2015.
3. Ben Taylor
A self-proclaimed ‘AI explorer,’ Ben has a unique mind that dives deep into the fields of NLP, deep learning, and data science. He specializes in genetic programming combined with automated network design and joined HireVue as their first data scientist. He also hates TensorFlow and Windows.
With over 13 years of ML experience, Ben tells students why most projects fail and has hands-on experience in scaling up Fortune 500 companies using the power of Big Data. The best part about his advice is that he focuses on the business side of building data science products rather than just sharing his technical expertise. For anyone interested in launching their own startup, Ben is an invaluable resource. You can follow him on the Clubhouse app to get professional opinions about jobs, insider info about the topics, and learn about topics nobody dares to discuss openly in the data science field. His willingness to be honest, open, and transparent with beginners is one of the cornerstones of his personality and you can see his professionalism shine through his work.
4. Eric Weber
Eric Weber is the head of experimentation at Yelp and has an MBA Degree. He teaches aspirants how to effectively adopt the mindset of a data scientist by striking a balance between theory and practical applications. With over 401k followers and being a former Senior Data Scientist at LinkedIn, Weber’s webinars are definitely worth a watch. He makes numerous appearances at conferences and on podcasts related to Data Science and even offers courses on various aspects of Data Science.
Eric tells students to embrace failures and have the mindset of continuous improvement. His one-hour fireside chat is a recommended watch.
5. Kevin Tran
Kevin Tran has more than 7 years of expertise in data science and machine learning. He completed his Bachelor of Science Degree in Materials Science and Engineering and graduated from Stanford University and has a strong understanding of marketing analytics. His career highlights include building a machine learning classification using Scikit-learn, Pandas, and Matplotib and he has worked on many sentiment analysis projects for classifying tweets using neural networks.
Most of his students connect with him over LinkedIn and what’s great about Kevin is that he has extensive experience working on various real-world projects for startups and large-scale ventures. He has been working as a Senior Data Scientist for Stanford University and is one of the top LinkedIn Data Science leaders in the category of Data and Analytics since 2019. He has also contributed to major companies like Dropbox, Google, Analyst.
6. Geoffrey Hilton
Geoffrey Hilton has been hailed as the Godfather of Deep Learning and has done exemplary work in the field of neural networks. He has a PhD Degree in Artificial Intelligence and has spent the majority of his time working for Google and the University of Toronto since 2013.
He is the author of the book ‘Neural Network Architectures for Artificial Intelligence,’ and is a graduate of the University of Edinburgh as well. Geoffrey has notable students he’s mentored in the industry such as Yann LeCun, Max Welling, and Peter Dayan all of whom are giants themselves in the Machine Learning field and postdoctoral researchers. He won the 2018 Turing Award and his research was affiliated with the University of Bristol according to citations by ResearchGate.
7. Dean Abbott
Dean Abbott is an internationally recognized data scientist with many accolades to his name. He is an expert in data mining and has authored ‘Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst.’
Dean is the co-founder and Chief Data Scientist of SmarterHQ, a Wunderkind company, and since 1987, he has pioneered innovative data science solutions in business and research fields. He is active on Twitter and has developed machine learning models for fraud detection systems, missile guidance, survey analysis, and more. Presently, he lives in the Greater San Diego area and runs a website known as ‘Abott Analytics.’
8. Andrew Ng
Andrew Ng has worked as the Chief Data Scientist at Baidu and as a Stanford University Professor. He is considered a leader in online education and Deep Learning since he founded Coursera, a platform that’s popular for running various MOOCs (Massive Open Online Courses).
He has authored many publications on Deep Learning and was the lead for the Google Brain Project. Andrew is an American businessperson and the founder of Landing AI. Landing AI is a company that empowers enterprises with SaaS products and AI solutions, thus letting them scale up and exceed client expectations. He’s a genius in what he does and a wizard when it comes to translating business requirements into real-world solutions using Deep Learning algorithms. He was named one of the most influential data scientists and was featured in Times Magazine multiple times for his contributions. A thesis on ‘Shaping and Policy Search in Reinforcement Learning’ was authored by him in 2003 and he wrote neural nets that could spot cats in YouTube videos.
9. Merv Adrian
Merv Adrian is the Vice President of Gartner and has more than 30 years of experience in the IT field. His focus lies on designing cloud-based products and has worked as a lead analyst for Microsoft. Merv has experience working with Apache Hadoop, Spark, relational and non-relational DBMS and various Machine Learning technologies. He has authored many guides on analytics query accelerators, information technology and programming, cloud database management systems, the best software development practices in the industry, and more.
Merv is an advocate of open source Machine learning software and shares his views actively about the impacts of data security on information platforms.
10. Fei-Fei Li
Fei-Fei Li is a professor of Data Science at Stanford University.
She has over 180 peer reviewed data science publications to her name and spearheaded the ImageNet project which was led by researchers from Princeton University. She served as the Chief Data Scientist for Google in the past and her interests lie in designing cognitive-based Machine Learning, computer vision, AI, and healthcare ambient intelligent systems.
Those who study Deep learning or are active in the data science global communities always hear her name and she has made appearances in top-tier conferences around the world. She is also the co-founder and chairperson of the non-profit organization AI4ALL which aims to diversify AI education and make it accessible to the global population. Her innovations from the lab have been featured in magazines and newspaper publications such as the Wired Magazine, Wall Street Journal, New York Times, etc.
Conclusion
Learning from the top data science leaders will by no means instantly elevate your career. However, from what we’ve gone through we can safely say that these influencers will play a big role in your academic progression. Data Science involves a mix of different disciplines ranging from software development, soft skills, and other technical areas.
This list is not an exhaustive one but gives readers a good idea of those at the top of the industry. Remember that Machine Learning is an industry that involves constant learning and growth. The best part about these names is that you can reach out to them on LinkedIn and connect directly for queries. If you need any insights, reading their publications and looking at their work will give you solid direction. You can boost your understanding by simply following these data science leaders profiles and their advice.
Apart from following these top data science leaders, you can also take up Great Learning’s Data Science and Business Analytics Course and upskill today. Learn from the best in the industry and power ahead your career.
1 Source: GreatLearning Blog
