5 Reasons Kaggle Projects Won't Help Your Data Science Resume


5 Reasons Kaggle Projects Won't Help Your Data Science Resume

If you're starting out building your Data Science credentials you've probably often heard the advice "do a Kaggle project". And, those folks are right, its a great way to start to get your hands dirty, playing with data and different techniques. Kaggle have also just released a new dataset feature, which makes even more data accessible to hack around with. However, when it comes to what to put on your resume to showcase your project work, don't rely on Kaggle as evidence of your commitment or credentials. Here's why:


  1. Its hard to stand out.. Unless you've achieved a very high position in one of the competitions (or have an impressive cumulative Kaggle profile), just doing the projects alone will not help your resume stand out. Given the thousands of other people also doing them, it is becoming harder and harder for merely working through them to be enough to differentiate you. You'll learn a lot, which is clearly important, but it won't make you stand out from your competition.

  2. You'll only demonstrate a partial Data Scientist skill-set. You are typically given a cleaned dataset, which makes it hard to demonstrate the full data science skill-set - from data munging through to analysis and model-building to results and conclusions. Given so much of a data scientist's time is actually spent extracting, cleaning, and manipulating data, working on an independent project where you can showcase you can do this (versus a Kaggle one) is more likely to pique the attention of a Hiring Manager

  3. Its likely not something you're passionate about. If you're interested in a topic / question you're going to put more time, thought, sweat into solving it. Its just a reality of human behavior! Countless Hiring Managers tell us that a candidate who's describing something they were genuinely really curious about, makes a huge difference in their application.

  4. It shows less initiative. If you're not coming up with the idea / topic to analyze (and instead taking it from Kaggle), you're immediately (inadverently) signalling a lack of initiative. Hiring Manager's love to see candidates with enough drive to initiate a project in order to learn more or solve a problem they have personally faced.

  5. It is likely irrelevant to the company. Only if you're very lucky will you be able to find and do a Kaggle project with direct relevance to the job you're applying for. Imagine how much more impacful your resume would be if you'd proactively come up with a topic, found data, and run some analysis on an issue you think the company might be facing? This truly gets Hiring Managers excited!


How to take action now?

Come up with independent project ideas. Start with a subject area you're interested in. Think of 5 questions you'd like to explore, and then get searching for some data to help you solve them. You may even find the dataset you need on Kaggle, but some good old fashioned googling should also help you out :)


Want to become a data scientist?

How would you feel if you woke up tomorrow with perfect knowledge, given your background and education, for how to become a data scientist as fast as possible?

Get started today because you will save time, money, and frustration with this
=> Data Science Getting Started Guide.



You might also enjoy these data science articles because you are terrific:


Sign up to receive the Data Science Weekly Newsletter every Thursday

Easy to unsubscribe. No spam — we keep your email safe and do not share it.