Must-Read Blogs for Data Scientists

Data scientists could be considered the magicians of the data world. With an array of math and data skills, data scientists translate raw data into valuable insights and make predictions for the future.

Since data science continues to become a more complex field as technology advances, data scientists are highly valued professionals in most companies. If a company wants to pull advanced analysis and make sound predictions based on their sets, then the organization will pour resources into their data science strategy. If you’re a data science professional, you’re guaranteed challenging, but rewarding work.

Top Data Science Blogs to Read

Data science blogs are a great way to learn more about the field. You get an inside perspective on what it’s really like to work as a data scientist, as well as the opportunity to stay up to date with all the happenings of the industry. Below are some of the top data science blogs you should know.

Beginners New to Data Science

Thinkful’s Blog - Data Science: Thinkful’s blog offers deep insights into what it’s like to become a data scientist. Learn from Q&A’s with Thinkful students, graduates, mentors, and experts in the field. If you’re new to the industry, our WTF is Data Science article gives everything you need to get an introduction to what skills you need, and what types of jobs you can land. Readers can also see how data science can predict current events like NFL touchdowns, job market insights, oscar winners, and more. And of course, you’ll get real stories about our Data Science Flex and Data Science Immersion programs.

FiveThirtyEight: You can find the most practical use of data there is on FiveThirtyEight’s blog. Get current data insights on economics, elections, politics, and sports. The name reflects the number of electors in US electoral college. The Editor-in-Chief is Nate Silver, a statistician and journalist currently serving as a Special Correspondent at ABC. FiveThirtyEight also hosts two podcasts about data points in politics and sports, so it’s a great way to start learning data science.

KDNuggets: Receive leading news information on big data, business analytics, and data mining with KDNuggets. As one of the most trusted data blogs on the web, they serve up fresh information daily. Find out the differences between machine learning versus deep learning, see what math skills you’ll need if you’re looking to enter the industry, and read about how data scientists are an important part of helping solve global pandemics. You can also get connected to top professionals in the field, find courses, jobs, and meetups.

Facebook Data Science Blog: No one knows how to play the algorithms quite like Facebook, so it’s worth checking out what their data science team has to say about the world of big data. Their frequently updated research blog offers a behind-the-scenes look at some of the major data problems being solved by the tech giant every day. Recent topics worth diving into include a look at their social good initiatives, insights into how people spend time on Facebook, and why it’s important to invest in research in the time of COVID.

Data Science 101: One of the OG data science blogs, the team here have been producing award-winning work since 2012.The founder himself transitioned from software engineering, so many of the posts offer an easy entry point to those just beginning their data science journey. There are a host of great posts, including intros into Google’s rules of machine learning, an ongoing series on cloud data science, and plenty of deep dives into the expanding world of AI. There is also plenty of video content, so you can learn in a style that best works for you.

What’s The Big Data?: What’s The Big Data? is where business breakthroughs, investments, and data science collide. Read about new data theories, suggestions for big data management and anything that helps evolve the IT/ data landscape. The blog was created by Gil Press, a former Senior Director in Thought Leadership Marketing at Dell EMC for over 16 years and current Managing Partner at gPress, a marketing, publishing, and research consultancy. If you’re interested in becoming a data scientist, this is also a good blog to check out because of the Q&A interviews with top data scientists in the industry. Current data science students:

r/datascience: If you’re studying data science and you’re not part of Reddit’s Data Science community, you’re missing out on a ton of valuable info and communication with people just like you. Get must-read advice on interview prep, check out an ever-expanding world of resources, find the answers to knotty problems, debate the usefulness of various tools in learning and so much more. With over 208,000 members, it’s an unmissable asset––as long as you’re prepared to lose more than a few hours lost in discussion.

FlowingData: If you’ve kicked off your learning, you’ll know that one of the more interesting parts of data science study is building out visualizations. FlowingData author Nathan Yau, who holds a Ph.D in statistics from UCLA, has been dedicating much of his time to building out COIVD data sets, looking at changes in airline flights, how social distancing works (and doesn’t), how stay-at-home orders change from region to region and more. Subscribers can also pay to unlock ‘The Process’, a newsletter filled with useful activities and lessons in modeling.

Kaggle: Wondering where data sets are that are used by data scientists? Kaggle is a site that allows you to search through thousands of public data sets to be able to conduct data science projects. You can also perform data science tasks with their large research database, and compete with other professionals. Not only do you get a chance to compete, but you also get to discuss information and get feedback from peers. If you're new to the industry, it’s a great place to start familiarizing yourself with raw data.

Data Science Report: Read about how a data scientist was hired at Airbnb, how banking and financial services fields scale their automation by using machine learning, all the way to recommendations on first data subjects to learn about in Data Science Report. Since the publishers, Starbridge Partners – a specialty executive search firm, are skilled in helping professionals land new careers, you can also find a solid data science job listings resource for once you finish studying.

Revolutions: If you’re an R advocate, the Revolutions blog is for you. The site is updated almost every day and is a can’t miss if you’re passionate about Python, machine learning and visualizations. It’s the place to go for weekly roundups on the latest software updates and insight into what’s going on in the industry, plus it has a frequently updated list of resources to help you as you learn. There’s also an extremely robust user directory, so you can find the data science group, and topic, you’re most passionate about––or you can start one of your own.

Data scientists in the workforce:

insideBIGDATA: If it’s happening in the world of machine learning, you can bet it’ll be covered here.There’s everything from podcasts to white papers, and you can get the scoop on advances in the industry, new AI forecasting methods, and a host of industry perspectives from data science experts. This is also the spot for all the major reviews from Harvard, KDD and insideBIGDATA themselves, thanks to their frequent long-form guides on everything from healthcare to using big data on an industrial scale.

Data Science Central: Get lost in the seemingly unending list of resources on Data Science Central. Become a member and work through a massive list of texts, including the Online Encyclopedia of Statistical Science, and Enterprise AI application perspectives plus guides to learning new skills like Azure, and Python regression and classification in a weekend. There’s also a host of podcasts on everything from machine learning to making decisions with analysis. More of a visual learner? Spend some time with one of their 222 webinars or join one of the many robust community groups and keep the conversation on big data going.    

Simply Statistics: Get the scoop from three industry titans and biostatistics professors, who have been sharing their data science knowledge since 2011. Explore the archives and you’ll uncover an insider's look at just how dramatically the field of data science has grown in the last ten years. Uncover how artificial intelligence is changing environmental health, see how massive amounts of data impacts our privacy, and check out how big companies like Netflix make decisions with data.

Dataconomy: Get industry perspectives on how data-driven technology impacts current events and our society. It’s a great resource to keep you connected with thought leaders in the space and what’s going on in media, data, technology, and business.

Datafloq: With Datafloq, you can learn about big data, blockchain, artificial intelligence and emerging technologies. Get info on topics like file transfer automation, data impacts on real estate, practical applications of augmented reality, and more. It’s a solid resource to learn more about the industry from expert contributors, and a good place to find data science events and job opportunities.

DataScience+: Get easy to use online data exploration tools plus a blog centered on data management, analysis, and reporting. The great thing about DataScience+ is that professionals can read about how data science is being applied in real world scenarios.

If predicting the future with data sounds intriguing, then it’s about time you learn more about Thinkful’s Data Science Immersion and Data Science Flex course. We’ll prepare you with all the skills you need to launch and thrive in a data science career – from a one-on-one mentor to a job placement guarantee.