Top 12 Data Science Experts and Best Data Science Career Articles on LinkedIn
Blog: Think Data Analytics Blog
So, you want to go for the “Sexiest Job of the 21st Century“? You should get started with LinkedIn. It’s not only a great place to network and find your next career opportunity.
LinkedIn is also a great site for learning and staying updated with the latest tools and industry trends. In order to build a great Data Science LinkedIn feed follow these top Data Science Experts on LinkedIn.
Top 12 Data Science Experts to Follow on LinkedIn
Vin Vashishta (21K Followers) – He is one of the biggest data science, machine learning, AI and deep learning stalwarts within the HR niche. He has got more than 20 years of experience and has built the most trusted brand in data science and machine learning. He is the founder and chief data scientist at V-Squared Data Strategy. His LinkedIn article How to Become a Data Scientist, No Matter Where Your Career Is At Now is a great read.
Andriy Burkov (33K Followers) – Andriy holds a Ph.D. in artificial intelligence and a data-fanatic. At present, he is the Global Machine Learning Team Leader at Gartner. His core interests include automated data analysis, machine learning, natural language processing, Linux hacking, effective database and search engine setup and querying. Do drop by his recent LinkedIn article – How to Become a Data Scientist in One Week. He’s got a great sense of humor and speaks fluent English, French, and Russian.
Kirk Borne is the current Principal Data Scientist at Booz Allen Hamilton and former professor in Astrophysics. Kirk Borne is one of top data science, data mining & machine learning influencers in the social media space. He usually posts the most recent, exciting and comprehensive tools, learning resources and news on big data, data science, artificial intelligence, and machine learning. I really admire his posts on learning and training resources. They usually act as goldmines for my own blog posts.
The contribution of Ronald van Loon in the field of digital transformation has been recognized by organizations such as Onalytica, Dataconomy, and Klout. He is also an author for a number of leading big data websites, including The Guardian, The Datafloq, and Data Science Central, and he regularly speaks at high-profile events and conferences. You must follow him if you are an ardent enthusiast of data science, big data, the IoT (Internet of Things), predictive analytics, and business intelligence.
Besides all the technical stuff, I found him very influential when it comes to the advocacy of customer service and customer experience. After all, a business can’t succeed if you are not making your customer happy, irrespective of your innovative work with data.
Vincent Granville (43K Followers) – a core Mathematician and lover of heavy algorithms, Dr. Granville is the founder of Analytic Bridge and Data Science Central. He is a former post-doctorate at the University of Cambridge and the National Institute of Statistical Sciences. You can learn a lot about data visualization, encryption methods, and randomness in quantum algorithms from his posts. His research work made a big impact on led the development of Hadoop and MapReduce.
Andrew Ng (159K Followers) – Andrew is the Co-Founder of Coursera and an Adjunct Professor of Machine Learning at Stanford University. His Machine Learning course on Coursera has more than a million subscribers, and he is one of the most passionate persons on the planet when it comes to deep learning, NLP, neural networks, and robotics. He is the former Chief Scientist at Baidu and the Head of Google’s Depp Learning project.
Tom Davenport (235K Followers) – the joint author of the post on “Data Scientist: The Sexiest Job of the 21st Century” along with DJ Patil. is a world-renowned thought leader and author, president’s distinguished professor of Information Technology and Management at Babson College, a Fellow of the MIT Center for Digital Business, and an independent senior advisor to Deloitte Analytics. You must follow him if you are into Precision Medicine and Personalized Healthcare.
Gregory Piatetsky-Shapiro (239K Followers) – he is the President of KDnuggets, one of the most comprehensive sites on data science and analytics. Gregory is a renowned expert on data science, data mining, and business analytics. He also co-founded KDD (Knowledge Discovery and Data mining conferences) and SIGKDD, the professional organization for Knowledge Discovery and Data Mining. Gregory has over 60 publications, with over 10,000 citations, including two best-selling books and several edited collections on data mining and knowledge discovery. By the way, he is little skeptical about Artificial Intelligence.
Carla Gentry (274K Followers) – Carla is currently the Digital Marketing Manager at Samtec Inc. Her career background in data analytics focuses on making actionable business sense out of large sets of numbers. She has got huge expertise in Comprehensive Customer Satisfaction and Retention Analysis, Brand Research and Competitive Analysis, Employee Retention Research, Database creation and mining, Survey Creation and Analysis (New Product and Branding). She also worked as a Freelance Data Scientist for more than 6 years during her illustrative career of 20+ years. In 2015, she was named as one of the most influential women in cloud computing.
Jules Polonetsky (314K Followers) – Jules focus areas are online data use, digital security, smart grid, mobile data, location, big data, apps, social media, connected cars, wearable tech and student privacy. He was formerly the Chief Privacy Officer at AOL. Of late, he’s been talking about the EU Privacy Shield.
Dennis R. Mortensen (350K Followers) – Dennis is the CEO and founder of x.ai, Visual Revenue, evonax and Canvas Interactive. He is the author of Analyzing for Data-Driven Insights. You can have access to webinars, workshops, and articles on AI, Analytics, MarTech & Marketing Analytics if you follow him.
DJ Patil (606K Followers) – former data scientist to the White House (first-ever national data scientist) now runs the big data product team for LinkedIn. By the way, he is the co-author of the exemplary post – “Data Scientist: The Sexiest Job of the 21st Century“.
Bernard Marr (1.1 M Followers) – Bernard Marr is a best-selling business author, speaker, and consultant in the big data analytics space. He is one of the world’s top influencer when it comes to big data analytics, KPIs, IoT, and digital transformations of businesses. He is also one of the top voices on Forbes, Data Science Central, and Smart Data Collective.
Best Career Guidance Articles on Data Science to Read on LinkedIn
The article “How to Kickstart Data Science Career” by Mahesh Babu Channa provides very practical advice to start a career in data science for both freshers and seasoned professionals. Among his top tips, he puts a strong emphasis on getting a Master’s degree (MS or MBA) with Business Analytics specialization. With more than 3,000 likes and 500 shares, no wonder why MS Business Analytics programs became so popular.
However, he has also put emphasis on building a strong foundation, acquiring strong skills in analytics, reading case studies on data science applications in business, and participating in data science competitions.
Alireza Yazdani also advised learning coding and machine learning in his article titled Tips for Aspiring Data Scientists. He also made a very valid point of excelling at MS-Excel and learning data visualization. I can’t agree on this more. Data is useless if you can’t understand it and/or make others understand. Data visualization is about how to present your data, to the right people, at the right time, in order to enable them to gain insights most effectively. His suggestions on the professional front make this article a must-read.
JT Kostman penned down 25 tips in his article – Advice for New Data Scientists. While reading the opening, I could relate myself as well regarding getting Inmails and queries regarding how to start a career or where to study. JT stressed on being smart, being passionate, being creative, and you must have the heart of a hacker.
I really loved his point on professional degrees – they can act as the ticket to a job. But, once hired, you need to apply your skills. He also advised giving priority to teamwork, continuous learning, presentation skills, and focussing on the fundamentals.
The key takeaways from the post on Top Data Science Skills in 2017 by Lillian Pearson are learning to code in R or Python, know how to use SQL for queries and reforming data, and know implementing machine learning for future predictions. In fact, Peter Eliason also stressed out on the importance of learning SQL in his article. In the modern era, data management tools like NoSQL and Hadoop are more popular. He has got point. To do well in the career you must know both.
Technical skills are no doubt important. But, to stand out in the competitive job market, you need to sharpen your soft skills as well. Know about 5 Essential Non-Technical Skills for Data Scientists by Gaurav Vohra. Kate Strachnyi also wrote about three curated tips in her post Advice for Aspiring Data Scientists. She also lobbied for getting started with the basics and working on real projects before jumping full-fledged.
Don’t Follow the Big Data & Data Science Trend Blindly
All the business organizations, including management consulting firms, banks & financial services, and tech companies, are indeed looking for big data talent. In fact, a recent IDC forecast shows that 2018 will see a six-time growth in the big data & analytics job market. Social media platforms are getting bombarded with blog posts and videos on data science, big data, and analytics. With a lot of hullabaloo going around, students and professionals are going crazy after data science and business analytics programs.
All the top and elite universities are re-structuring their program-curriculums. But, on the dark side, all these fuelled the mushrooming of the specialized Master’s programs in business analytics and data science all around the world. Don’t forget about online courses that pop up on your screen every time you check websites or Facebook feed.
The businesses might need around one million data scientists by 2018. As per IBM predictions, the number of jobs for all US data professionals will increase by 364,000 openings to 2,720,000 by 2020. But, businesses do have options for training employees on the job. While companies like IBM or Deloitte are extensively collaborating with business schools to design MBA & MS programs, companies like Booz Allen Hamilton and Qlik are focusing on creating data scientists in-house.
Since data science combines analytics with business acumen, much can be gained by targeting employees with domain expertise, in addition to technical prowess. For many organizations, the best use case for data science to add business value remains marketing and technology platforms with high activity levels.
“ Rather than worry too much about having too few data scientists, we should worry about whether our senior managers are numerate enough and whether we have enough critical thinking skills across the whole workforce.” – Clive Holtham, Cass Business School
Last but not the least, don’t commit the mistake of enroling for an MS Data Science or MS Business Analytics program just because the courses are trending and pay well.
Do take caution and self-evaluate yourself. Don’t mix enthusiasm/trends with passion. Trends keep changing. don’t follow the data science (or big data) hype blindly. Besides, passion is not always good enough. You must possess the talent and need to be good at particular tasks. If you don’t possess a strong aptitude, quantitative background, and programming skills, Data Science & Analytics might not be your cup of tea.
If you need assistance with identifying the right program or cracking the admission procedure at the top universities, just give me a shout. You could also share your thoughts and/or queries in the comments, and don’t forget to share the blog post
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