5 Free Resources to Master Your Data Science Job Search

Being in the job search is difficult, there are no two ways to do it. Sending out resumes, rewriting cover letters, waiting endlessly between applying and waiting for a response (or just getting fooled) is no fun.

The good news is that it's a lot easier than it used to be. It is no longer necessary to physically send or deliver letters; You can make many applications with just a few clicks. There are many specialized job boards, interview preparation tools, and additional resources to make you more likely to find, apply for, and land the data science job of your dreams.

Let's talk about the best free resources at your fingertips to land that job in data science.

It doesn't matter how brilliant your resume is if you don't have the skills to back up your credentials. One of the best ways to learn data science skills is by doing your own projects.

Sometimes it's hard to get ideas for data science projects, which is where Kaggle enters. Kaggle hosts a huge registry of datasets, machine learning competitions and includes answers and different approaches on how to approach various projects.

Fountain: https://www.kaggle.com/datasets

It's a great resource because it allows you to apply your data science skills in practical scenarios, receive feedback, and learn from others' solutions. Not only that, but if you actually win a Kaggle competition, that can serve as a kind of flexibility for any employer. Most data scientists know Kaggle and will be very impressed that it can address those problems.

In short, the most valuable asset Kaggle provides is data and real-world problems. It offers valuable exposure to industry-level issues and the opportunity to gain the attention of major companies.

I may be a little biased here as a founder of StrataScratch, but I founded the company because I noticed a real problem: it's hard to prepare for data science interviews. So I started collecting interview questions from as many different companies as I could and sorting them by difficulty, question type, and company. The result is a database of over a thousand real-life interview questions (both coded and uncoded), plus solutions if you're really stumped.

In my experience interviewing for data science jobs, it's not just about having the skills, but also being able to stay calm and think about everything that comes your way. As you can imagine, it's much easier to do this if you've seen the interview question (or some variation of it) before.

It's also a good idea to practice interview questions at every stage of your data science job search, not just when you have an interview scheduled. Practicing IRL interview questions gives you an idea of ​​the problems data science companies are interested in solving, as well as the skills you should focus on learning or honing.

Fun fact: while edx and Coursera If we have very expensive data science courses, you can get the same knowledge absolutely free by simply auditing the courses. Now, this means that you don't get a certificate of your achievements, which can definitely be valuable, but you do get top-notch lessons, tutorials, and guides for free.

Fountain: https://www.edx.org/verified-certificate

Simply search for the course with the information you are interested in and enroll in audit mode. You can use this to strengthen weak points on your resume, learn skills to complete projects for your portfolio, or simply explore a topic you are passionate about.

You're reading this on KDNuggets, so you should already know that it's a useful resource for getting a job in data science. However, KDNuggets doesn't just offer blog posts. There are datasets (again, useful for projects), virtual and live events (great for networking), programming cheat sheets, and curated tool recommendations.

I'm launching Towards data science, too, as it is another blog full of tutorials, guides, how-tos, personal stories and experiences, and more. While some stories have a paywall, many are left free. You can easily navigate the TDS home page and look for free stories that don't have a little star next to the author's name.

In short, one of the best ways to get a job in data science is to learn from other data scientists. Many of them are kind enough to post content online for free for you to read and enjoy.

Not sure where to start your data science job search? Classic contenders like LinkedIn and Indeed definitely win in terms of volume, but I love well found to find data science jobs for the curated aspect.

Wellfound has some advantages over other job boards. First, the filtering options are powerful. You can easily find jobs based on investment round, salary, equity, markets, company size, and more.

Second, these are mainly startups. If you've tried and failed to land a FAANG job, it may be time to look at a different scene. Startups are hungry for data science talent, and if you can broaden your horizons to consider a slightly less conventional employer, you might have better luck.

Three, it's a little newer and fresher, so I think it's a better job search experience. Features include telling you who invested in the company, how recently the recruiter was reviewing applicants, and getting statistics from Glassdoor on leadership ratings and work-life balance.

Fountain: https://wellfound.com/

Job hunting is never fun, and it seems like this year has been worse in terms of shell companies, making you go through multiple rounds of interviews only to be told that the position was actually filled internally or just directly. publish non-existent jobs to look better to potential investors. Maybe you've even come across a fraudulent job advertisement.

Hopefully, this list of free resources will make your life a little easier. With these five free tools, you'll be better equipped to find and land your ideal data science job.

twitter.com/StrataScratch” rel=”noopener”>twitter.com/StrataScratch” target=”_blank” rel=”noopener noreferrer”>Nate Rosidi He is a data scientist and in product strategy. He is also an adjunct professor of analytics and is the founder of StrataScratch, a platform that helps data scientists prepare for their interviews with real questions from top companies. Nate writes about the latest trends in the career market, provides interview tips, shares data science projects, and covers all things SQL.