You’ve succeeded in acquiring the academic knowledge needed for the bottom tier of the Successful Data Scientist Pyramid. Everyone accepts that you are too young in your career to have extensive domain knowledge that is the the top tier of the Pyramid. As an early career data scientist how do you get the working knowledge or the middle tier skills to prove your abilities and secure your first job?


This data science platform has over 5 million users across 194 countries. It has emerged as a method for data science practitioners to sharpen their skills. Recruiters have begun to use Kaggle achievements as one of the metrics to gauge the competitiveness of candidates.

ExplodingTopics.com listed the 7 Key Data Science Trends for 2021-2025. They included concerns about deepfake videos and audios, consumer data protection and AI developers combating adversarial machine learning, as well as the expected increase in apps in Python, the hiring of more data analysts and the increasing demand for end-to-end AI solutions. The seventh trend for the next 5 years? Data scientists joining Kaggle.

6 Benefits of Kaggle

TowardsDataScience.com gives you the six reasons “everyone” uses this website and “why you should, too.”

  1. Data – A variety of data sets are available for your use. Most are in the CSV file format but other formats exist as well, allowing you to practice working with them.
  2. Code – One of the best and most plentiful features of Kaggle. You can see code examples and can easily search Notebooks for code as well as text comments by users and coders. Most code is in Python but R, SQLite and Julia are available as well.
  3. Community – Learning from other data science professionals is often cited as a reason to participate in the Kaggle community. “Apart from the programming skills and implementation of ML algorithms, candidates can also learn to approach the problem statements and the datasets with multiple solutions created by others,” says Vidhya Veeraraghavan, head of analytics at Standard Chartered.
  4. Competition – Kaggle offers competitions that allow you to test your skills, see how you rank amongst peers or make some extra cash. “I used Kaggle competitions to see how I would perform with little data science knowledge versus performing with nearly two years of data science experience. As you can imagine, I improved considerably,” says Matt Przybyla, Senior Data Scientist.
  5. Courses – Kaggle offers 14 data science courses which include the obvious and necessary ones of Python, Pandas and Intro to Machine Learning but also some SQL courses and the more advanced NLP and Game AI and Reinforcement Learning.
  6. Inspiration – Following a competition with an interesting result can be very inspiring. If you are personally stuck on how to perform a certain function or solve a problem, it is great to have someplace/someone to turn to for help. Solving a problem and creating better solutions is always inspiring to the data scientist. Kaggle makes this possible.

Usha Rengaraju, India’s first female Kaggle Grandmaster and a data scientist consultant, says, “Dedication, consistency, innovation, out-of-the-box thinking, ability not to give up and collaboration – all these are key traits of a top kaggler, and they are also the key skills which any employer may look for.”

Interested in conducting a data science job search? Contact Smith Hanley Associates Data Science and Analytics Recruiter, Paul Chatlos at [email protected].


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