Hello friend! I wanted to pull together this detailed guide highlighting my top data science influencers that I highly recommend subscribing to on YouTube.
As an experienced cybersecurity architect at a major cloud services provider and longtime tech blogger, I encounter fascinating intersections between the data and security worlds everyday.
The exponential growth of data combined with surging adoption of analytics and AI models is creating huge opportunities in data science careers. However with upside comes risk if appropriate data protections aren‘t baked in.
So beyond just software libraries and statistical methods, considering privacy, ethics, governance, and security will prove critical for long term success. We have huge collective responsibility!
That’s why I appreciate data influencers that discuss the bigger picture implications of our work, not just coding tutorials. With the power of data comes great responsibility.
Let me introduce you to 10 of my top picks covering both strategic and technical topics worth tuning into. I included helpful background, content overviews, video suggestions and more so you can find the right fits for your interests and experience level.
I’m confident you’ll leave armed with new knowledge resources to skill up in this rewarding and complex field! Now onto the experts…
Ken Jee – The Data Science Athlete
With a Masters of Science focused on Machine Learning from Columbia University and 7 years working in analytics at UnderArmour headquarters, Ken Jee offers incredibly valuable insider perspective.
He focuses keen attention on sports analytics given his athletic background and past work optimizing athlete health/performance through data-driven insights. I‘m especially impressed by some of his innovative techniques leveraging sensor data.
For example in this featured video, Ken discusses a predictive model identifying injury risk factors for athletes based on wearable usage trends and associated tweak suggestions to reduce probabilities through selective training regimen adjustments. Really fascinating stuff!
Beyond his 136k YouTube subscribers, Ken also curates a weekly newsletter called Data Science Weekly highlighting the latest developments across sports, health, and general analytics domains. Well worth the subscription to stay aware!
Ken‘s Key Stats:
- 136,000 YouTube Subscribers
- 25+ Videos
- Columbia MS in Machine Learning
Areas of Expertise: Sports Analytics, Health Analytics, Wearables Data
Alexey Grigorev – The Data Science Coach
As both a seasoned practitioner and adjunct lecturer at the Swiss Federal Institute of Technology, Alexey Grigorev offers uniquely well-rounded mentorship.
With 350k subscribers and counting, his main focus areas include:
Python Programming: Alexey has an extraordinary ability to break down complex coding concepts into easily-digestible tutorials for data manipulation, analysis, and machine learning modeling. I learned a ton refreshing my Python skills!
The Business of Data Science: Going beyond just analytics, Alexey explores product management, presentations, team leadership and translating technical outputs into compelling business value. This translates well into the workplace.
Emerging Trends: As an author pursuing a 2nd Masters focused on deep learning, Alexey delivers bleeding-edge commentary on things like MLOps, Causality, Distributed Computing, and Privacy Enhancing Technologies (PETs). Well aligned to my interests!
For beginners, I highly recommend his basics course:
Data Science Project from Scratch in Python
Alexey‘s Key Stats:
- 358,000 YouTube Subscribers
- 28+ Hours Content
- Masters of Data Science from Netherlands
- Ex-Chief Data Scientist at OLX Group
Areas of Expertise: Python, Emerging Trends, DS Project Breakdowns
Sundas Khalid – The Self-Taught Data Scientist
As a former music major that leveraged online resources to successfully land senior data science roles at both Amazon and Oracle without formal technical training, Sundas Khalid offers an incredibly unique blueprint for others looking to transition careers.
She provides curated recommendations across courses, books, blogs and tools that enabled her to gain demonstrable data skills starting from scratch. I love that the plans are prescriptive – actually detailing specific milestones and checkpoints. No fluff!
As a hiring manager, I also appreciate Sundas’ transparent perspective on resume writing, interview prep, negotiation and job selection considerations oriented towards self-taught professionals. She reverse engineers what tech leaders are actually looking for. Extremely helpful insider tips!
For those evaluating career changes, I’d specifically suggest:
How to Learn Data Science for Beginners
Sundas’ Key Stats:
- 117,000 YouTube Subscribers
- 15+ Videos
- Ex-Senior Data Scientist at Amazon
- Computer Science Beginner
Areas of Expertise: Transition Roadmaps, Self-Directed Learning, Resumes/Interviews
Data Professor – Unlocking New Medical Frontiers
With a PhD focused on Bioinformatics and Master‘s degrees spanning Statistics, Genetics, and Computer Science, Dr. Chanin Nantasenamat puts the "Professor" in his YouTube persona demonstrating true subject matter authority.
As a pioneering researcher leveraging data science techniques to accelerate medical innovations at multiple Thailand universities, Dr. Nantasenamat provides uniquely advanced tutorials on things like genomic sequencing analysis for precision medicine, neural networks for cancer detection, and pharmacology imaging analytics.
I‘m endlessly impressed by projects like his work leveraging drone imaging and crop disease object detection models to provide low-cost preventative diagnostics/alerting for rural farmer communities. Chanin discusses the initiative and reflects on lessons learned in this featured video:
Using Drones and Artificial Intelligence to detect crop diseases and pests
Chanin‘s Key Stats:
- 217,000 YouTube Subscribers
- 100+ Videos
- PhD in Bioinformatics
- University Professor
Areas of Expertise: Healthcare AI, Genomics, Medical Imaging
Data Science Jay – Tackling the Interview
With Data Science program design experience across General Assembly, Flatiron school and Thinkful, Jay Oh began focusing intensely on preparing data professionals specifically for the interview process through his platform Interview Query.
There‘s no sugarcoating – successfully landing a top data science role requires nailing complex case walkthroughs spanning statistical analysis, model evaluation, technical recommendations and process communication under tight timelines.
Jay develops detailed sample studies with actual datasets and then methodically works through solutions while explaining each step – simulating the actual high pressure environments.
As someone who regularly conducts screening across our own analytics team, I think Jay‘s content mirrors actual interviews remarkably close. Watch a few examples and you‘ll see firsthand!
For interview practice, check out questions like:
Technical Data Science Interview: Product Analytics | Data Science Product Metrics
Jay‘s Key Stats:
- 133,000 YouTube Subscribers
- 74 Videos
- Data Science Program Designer
- Founded InterviewQuery.com
Areas of Expertise: Data Interview Prep, Portfolios, DS Project Walkthroughs
