Having a good mentor can be a major catalyst. A mentor can help you sort the signal from the noise—the hype from reality. They can reduce the information asymmetry inherent in the job market, guide you towards the best resources and tools, and help you sell yourself to hiring managers. Whereas a data science course meant for mass consumption must have broad appeal, a mentor can give you advice specific to the role and domain you are aiming for.

A graduate degree doesn't make you better prepared for the job market—at least, not enough to justify the cost in both time and money. Yes, you will learn a lot. But you can learn just as much—if not more—from free online courses (having a good mentor helps too). However, having a degree—the higher the better—gives you a leg up in the job market. And that's because education is valuable to employers as a signal.

Finding a mentor can be transformational. That's why we continually try and make it as easy as possible to do just that on SharpestMinds. But once you find the right mentor, how do you ensure that you get the most out of the experience? Here's what we've learned from our most successful pairings.

If you're setting out on a journey to mentor someone, keep in mind that your behavior will have an outsized influence and impact on the person you're mentoring.Here are 5 lessons we've learned about what makes a great mentor.

Landing a job as a data scientist, machine learning engineer, or really any kind of role writing software takes more than just math and programming knowledge. In reality, these roles require you to make hundreds of decisions every day.

In March 2020, COVID-19 hit the world economy. Here's the effect it had on data science hirings, firings, and payscales.

The kinds of questions you'll get asked during behavioral interviews, and how to think about answering them.

How is interviewing at consulting companies different from interviewing at product companies?

A Q&A about how to do a proper train / test split with time series data.

Our mentors and mentees discussing the hardest questions they've ever been asked in their job interviews, and how to answer them.

Why data science job descriptions can be so inaccurate, and how to tell which postings you should apply to.

Understanding the hiring process from the inside, and what it means for your application.

How to build a project that employers will actually care about.

On the value of the PhD, the Master's, and when it's time to drop out.

Stories of personal data science projects that led to job offers.

Tips on how to focus your skills development, and find the right kind of data science job.

Getting noticed in a world of unremarkable people.

Everything you need to know to become a machine learning engineer from scratch.

Announcing the launch of the SharpestMinds mentorship program!

Common resume mistakes to avoid if you want to keep your application out of the "no" pile.