With over 690 million users, LinkedIn has become the go-to platform for professionals looking to build their networks and further their careers. For data scientists, LinkedIn can be an invaluable resource for staying on top of the latest trends, connecting with leaders in the field, and showcasing your skills to potential employers.
But with so many data scientists on LinkedIn, how do you identify the top influencers that are worth following? In this article, we provide a rundown of 10 data scientists who stand out for their expertise, thought leadership, and ability to inspire others in the field.
How We Selected the Top Data Scientists on LinkedIn
To compile this list, we looked at several factors including:
- Number of LinkedIn followers
- Frequency of posting valuable insights and content
- Level of engagement and discussion generated
- Real-world experience and accomplishments
- Quality of content and perspectives shared
Based on these criteria, here are 10 data scientists that rose to the top and are absolutely worth following on LinkedIn.
1. DJ Patil
With over 128,000 followers, DJ Patil is one of the most recognizable data scientists on LinkedIn. He boasts an impressive resume, having previously served as the first Chief Data Scientist of the United States under President Barack Obama. At LinkedIn, Patil provides unique perspectives on technology, healthcare, innovation, and of course – data science. His posts generate plenty of discussion and he frequently weighs in on trends like AI, machine learning, and big data analytics.
2. Hilary Mason
Hilary Mason has founded several high-profile startups including Fast Forward Labs and Data Robot. With over 91,000 LinkedIn followers, she offers valuable insights on data science and machine learning. Mason posts regularly about technical concepts, her speaking engagements, and developments in artificial intelligence. She also openly shares career advice for aspiring data scientists.
3. Kirk Borne
As one of the most influential data scientists on LinkedIn with over 430,000 followers, Kirk Borne’s posts generate significant discussion. Borne has decades of experience in astrophysics, data mining, and data analytics. He offers unique perspectives on the intersection of data science and space research. Borne currently heads up the Data Science team at Booz Allen Hamilton and frequently shares valuable content on big data, analytics, AI, and the IoT (Internet of Things).
4. Monica Rogati
Formerly the VP of Data at Jawbone, Monica Rogati now works as an AI and data science consultant. She posts frequent updates on data science news and trends to her 140,000+ LinkedIn followers. Rogati’s content provides thoughtful perspectives on analytics, AI, wearables, IoT applications, and data ethics. She excels at simplifying complex concepts and technologies for the everyday LinkedIn user.
5. Pete Warden
With extensive experience at Google and Apple, Pete Warden is an expert in applied machine learning and interpreting large datasets. He shares practical data science insights and trends with his 50,000+ LinkedIn followers. Warden’s posts highlight the business implications of technology like self-driving cars and image recognition. He also provides valuable commentary on the ethical considerations surrounding big data and AI.
6. Vincent Granville
As the co-founder of Data Science Central, Vincent Granville is highly influential in the data science landscape with over 330,000 LinkedIn followers. His posts explore topics like machine learning, statistical modeling, data mining, APIs, data visualization, and programming languages like Python and R. Granville examines practical applications of data science in fields like finance, healthcare, retail, advertising, and more.
7. Gregory Piatetsky
Known as a pioneer in data mining, Gregory Piatetsky has over 290,000 followers on LinkedIn. He is one of the most followed data scientists on the platform. Piatetsky provides insightful commentary and posts on data analytics, machine learning, AI, predictive models, IoT applications, and big data platforms like Hadoop and Spark. With decades of experience, his perspectives carry significant weight in the data science community.
8. Carla Gentry
Currently the Analytics Solutions Director at Tableau, Carla Gentry leverages her background in statistics and computer science to provide valuable data insights to her 50,000+ LinkedIn followers. She covers innovative topics like visualization, self-service analytics, VR analytics, drone data, and practical applications of data science. Gentry also openly shares career advice specifically for women working in technology and data roles.
9. Michael Li
Michael Li founded The Data Incubator, an eight-week data science training bootcamp placing students in roles at top companies. With over 160,000 followers, Li provides valuable perspectives on machine learning, big data case studies, predictive modeling, recommendation systems, and other practical data science applications. His posts also highlight the latest trends in data science hiring and training.
10. Jeremy Achin
As co-founder and CEO of H20.ai, a leading AI platform, Jeremy Achin has over 140,000 LinkedIn followers. He posts frequent updates on innovations in AI, machine learning, and data science. Achin provides thoughtful commentary on automating machine learning, trends in predictive analytics, challenges facing AI adoption, and other valuable insights for data professionals and business leaders alike.
5 Key Takeaways from the Top Data Scientists on LinkedIn
Although their backgrounds and areas of expertise vary, a few key themes consistently emerge from the top data scientists on LinkedIn:
- Machine learning and AI will revolutionize virtually every industry and profession in the coming years.
- Data collection methods and datasets are rapidly expanding from sources like IoT, sensors, wearables, mobile, social media, and more.
- Data visualization and interpretation are becoming increasingly critical for extracting insights and communicating data-driven solutions.
- While data science automation will enable new possibilities, human oversight is still essential for many applications.
- Data ethics, privacy, algorithmic bias, and security require more consideration as data analytics grows more sophisticated and ubiquitous.
These influential data scientists stay ahead of trends in the field while thoughtfully examining the implications of new technologies through their LinkedIn posts. Following them provides unique visibility into the current landscape and future trajectory of data science.
How to Get the Most Value from LinkedIn as a Data Scientist
Beyond just following top influencers, here are a few tips to maximize the impact of your LinkedIn profile and feed as a data scientist:
- Showcase projects: Highlight your data analytics, modeling, visualization, and storytelling skills through concrete examples.
- Join relevant groups: Weigh in on discussions and connect with like-minded professionals through groups focused on data science, machine learning, AI, and more.
- Publish on LinkedIn: Share your perspectives and establish your voice by publishing long-form posts.
- Follow companies: Monitor hiring trends and job postings by following key companies in your industry.
- Expand your network: Connect with other data scientists and business leaders who can provide value – and vice versa.
The data science community on LinkedIn is continuing to gain influence as more organizations embrace advanced analytics and AI. Tap into these connections to enhance your learning, propel your career, and keep pace with tech breakthroughs.
Conclusion
LinkedIn provides a valuable platform for data scientists to exchange insights, further their careers, and stay on the cutting edge of developments in AI and analytics. By following thought leaders like DJ Patil, Hilary Mason, Kirk Borne, Monica Rogati, Pete Warden, Vincent Granville, Gregory Piatetsky, Carla Gentry, Michael Li, and Jeremy Achin, data professionals can keep their fingers on the pulse of the field.
The influential data scientists on LinkedIn generate discussion, share practical use cases, and provide thoughtful commentary on emerging trends. While their specialities range from machine learning to visualization and ethics, together they represent diverse perspectives on data science. Following a mix of these respected leaders can help propel your career while expanding your analytics skillset.
