I still remember the defining moment when I decided to transition from physics into data science during my final year in university.
The jump was… scary.
The self-doubt was real. The fear was real.
Believe it or not, I was just like any other aspiring data scientists who started out by learning from online courses, reading relevant textbooks and joining Kaggle.
But I still felt something was missing.
Throughout that period, I had been learning by myself without really understanding how data science “works” in real world and how to become a great data scientist.
I felt that I needed some guidance. I needed to learn from mentors.
And this was when I started learning from the data science leaders on LinkedIn, which tremendously helped in my learning journey and even boosted my data science career to the extent I’d never imagine possible with abundant learning opportunities.
In fact, they are the reason why I’m giving back to the data science community by sharing my experience, knowledge and even my mistakes on LinkedIn and Medium.
If you’ve been following my articles, I shared the first list of data science leaders to follow one year ago and the list is by no means exhaustive, hence the writing of this article on top of that.
If you’re in data science field, I strongly encourage you to follow these giants — which I’ll list down in the section below — and be a part of our data science community to learn from the best and share your experience and knowledge.
Trust me, learning from these giants could turn out to be one of the life-changing decisions you’ll ever make (at least for me).
Enough of talking… Let’s get started!
She currently works as a Chief Decision Scientist at Google who is also an expert in the intersection of statistics, data science, and AI.
Personally, I think she is seriously a rare breed for having deep technical expertise while — at the same time — having the capabilities to break things down into simple ideas for people to understand.
Her thought leadership and ideas in the fields of machine learning, artificial intelligence, and data science have never failed to amaze me as they always give me new perspectives and knowledge which I’d not know have learned from anywhere else.
And that, my friend, is the power of learning from others (aka mentors).
If you’re interested in learning from Cassie — which I highly recommend — check out her posts, articles and videos on Linkedin, Medium, Twitter and YouTube.
In fact, she was the one who inspired me to write this article — P-values Explained By Data Scientist — after watching her sharing on p-value!
What is a p-value? (by Cassie Kozyrkov)
Ben is a good friend of mine and we first met on LinkedIn during a discussion of certain data science topics.
He is a veteran thought leader around AI with over 16 years of machine learning experience.
He currently works at DataRobot as a Chief AI Evangelist — and yes — he is the go-to guy if you want to learn more about AI and understand the latest trend in this field.
Ben — in my opinion — is by far one of the sharpest minds in the field of AI and he constantly demystifies some of the common misunderstanding in this field with the goal of democratizing the use AI.
If you did video interviews using HireVue requested by companies before during your job search journey…
Ben was the one who led the data science team and developed the first video interview prediction engines called HireVue Insights, and many more AI products!
I’m sure you’re familiar with Dat Tran if you’re active in the data science community on LinkedIn as he constantly shares the latest technology and deep learning updates to the public with a lot of great advice.
If you still have no idea who he is. Do yourself a favour. Check out his sharing on Linkedin and Medium!
When I first started out in data science, Kevin was one of the first few data scientists that I met on LinkedIn by sharing our thoughts and learning from each other.
His broad experience in working at various tech startups and deep expertise in developing credit and risk models further justify why I love his sharing so much.
Also, His advice to become a great data scientist in real world environment — technical or non-technical — has been tremendously practical and helpful to my learning journey as we continue to grow together.
Follow his advice and you’ll know what I mean. 😄
I’m sure this name sounds familiar to you if you’ve ever taken data science courses on Udemy.
When I first got started in my data science journey, I didn’t get started by reading a textbook, I didn’t get started by learning from Kaggle.
Instead, I got started by taking this online course — Python for Data Science and Machine Learning Bootcamp taught by Jose Marcial — that gave me a strong foundation and understanding of data science and machine learning in general to move forward.
He is one of the best course creators and instructors that I’ve seen so far and his courses are easy to understand and most importantly, practical to get you started!
If you’re a beginner in data science and want to know gain a better understanding of what this field looks like as well as its applications, then check out his course.
From his humble beginning as a fresh economics graduate to becoming an expert in data science training, instructor and consulting, helping companies build up in-house data science capabilities, is so inspiring!
More interestingly, he is also the co-founder of DataScience SG — one of the largest and active Data Science meetup group in Singapore.
The goal is to educate the public on what to expect from data science, what the job of data scientist truly consists of and also helping business to understand how they can benefit from data science.
I personally went to the meetup a few times for different topics as well as to network with professionals in this space. Definitely the best meetup ever as everybody is so welcoming and has the hunger to learn and grow together.
What’s even more mind-blowing is that he did podcasts both as a guest with Joe Rogan (part 1 & part 2) and as a host (Artificial Intelligence podcast with, for example, Elon Musk) before.
If you want to understand more about the interaction between human behaviour and AI, or you want to stay at the forefront of AI technology and applications, check out his podcasts, YouTube channel, and of course, his LinkedIn posts where he shared meaningful insights on AI.
Personally, I find his podcasts and Linkedin posts very insightful, especially on the evolution of AI and its interesting connection with human behaviour.
Currently Kristen Kehrer is a Data Science Instructor at UC Berkeley Extension and the founder of Data Moves Me.
Throughout my whole data science career, Kristen has been my role model/mentor to learn from with her deep experience and knowledge in SQL and analytics space.
In particular, I love the discussion between her and other prominent data scientists like Favio Vázquez on LinkedIn and most importantly, the podcast interview — Humans of Data Science (HoDS)— with Kate Strachnyi!
As you may have already realized, the data science community on LinkedIn is a close-knit community where we interact with one another to share and learn together.
Srivatsan is currently a Chief Data Scientist/Architect at Cognizant.
His experience in building complex analytical pipelines, machine learning models for extremely complex business process, and helping companies with transformation in data and analytics space, has definitely boosted my understanding in many areas in big data, cloud, and AI.
Reading his insightful posts on LinkedIn has been one of the most rewarding learning activities to constantly keep myself updated with the latest AI technology and the best practices in data science space.
Check out his posts and you’ll know what I mean. I know you’ll love them.😅
As long as you’re on LinkedIn and looking for data science posts (or content in general) to learn from, chances are you may already have known David.
Besides being a VP of Analytics at Schedulicity, he is also famously known for his great data science teaching as an instructor, blogger and YouTuber.
My vision is a world filled with data literate professionals. — David Langer
He is a huge advocate of 20% of analytics that drive 80% of ROI.
Personally, I’ve been learning a lot from his sharing on LinkedIn and I’d say he is definitely one of the prominent educators in data science space.
Thank you for reading.
There’s a long list of data science leaders to follow here, isn’t it?
Learning from mentors who have walked the path will save you tons of time compared to learning everything on your own. Even better, you’ll be well equipped with the knowledge of data science (technical & soft skills) as well as how to become a great data scientist.
And of course, the list of data science leaders here is by no means exhaustive. These are just some of the top data science leaders whom I’ve been following and learning from since the beginning of my data science journey.
And I hope you’ll find their sharing insightful and helpful to you.
⭐ Comment below if you know any other data science leaders that we should follow!👇🏻
Inspired by their contribution, I’m giving back to the data science community by sharing my knowledge and experience along the way to hopefully help more aspiring data scientists.
At the end of the day, we — as a part of the data science community — are here and will always be here to share, help, learn and grow together.
And this is what a community is meant to be.
I hope you enjoyed reading this article and I look forward to having you as part of the data science community.
Remember, keep learning and never stop improving.
As always, if you have any questions or comments feel free to leave your feedback below or you can always reach me on LinkedIn. Till then, see you in the next post! 😄
“Top 10 Data Science Leaders You Should Follow”– Admond Lee Tweet