How to Find Great Data Science Jobs in 2024?

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Dessie Tsvetkova 16 Jan 2024 9 min read

Data science is one of the most sought-after careers in the world right now and there is a good reason for that. Just look at Glassdoor’s ranking for 2022 – data scientist is the third best job in the US. But it shouldn’t be a surprise. In a world filled with data, positions in this exciting, evolving field are ripe for the picking.

And yet, such demand can make the job hunt more overwhelming. To absolute beginners and students in data science, the process might seem impossible. Even those data scientists at entry-level or mid-level positions can struggle with the next step in their career path. That is why, we aim to ease some of the pressure by showing you how to find great data science jobs.

In this article, you will find a number of useful resources for job-hunting like:

  • Where to look for job openings
  • What it takes to be a freelancer in data science
  • How to successfully network online and at industry events

Job Boards

Almost like a primal instinct, these online directories are the first port of call for most job seekers out there. The same applies to novices who are looking to break into data science. One reason for that is because they’re well-known and easy to filter.

We’ve compiled a selection with some of the most well-organized, effective job boards. Not only do they have a proven track record of success, but they also boast a myriad of listings by reputable companies and emerging exciting startups alike.

General Job Boards

These websites will be familiar to many, no doubt, as a large percentage of seekers will take to them first. Some popular online job boards include:

Indeed

Indeed is the largest job platform where you can find millions of jobs online to find the next step of your career. The websites allows you to filter, sort, and save the listings that catch your eye. There’s an option of uploading your resume or building it from scratch, and most times you can even apply to jobs directly on the website.

Glassdoor

Glassdoor houses millions of job opportunities in an array of fields, as well as insights and reviews about the company you’re applying for. In the company’s own words, the website empowers job seekers with straight-from-the-source information regarding the places you’re applying for.

Monster

Monster is a great source for career opportunities that fit your needs, no matter which field you’re interested in. Along with job openings, they also offer services like a salary tool, career advice, resume help, and more.

Muse

Unlike our previous examples, Muse is more like a database that shows you current job opportunities that you can take advantage of. While you can’t apply directly on the website, there are many filters to narrow down your desired role by title, industry, location, salary, etc.

LinkedIn

LinkedIn is considered the social media for professionals, where people post about their professional lives and achievements. Only the well-versed know it also boasts a rather extensive list of job opportunities, including the chance to apply directly with your LinkedIn profile, or the chance to chat with recruiters directly in order to gain a competitive advantage.

University Job Boards

Another job board that perhaps isn’t as popular, but still worth a look is your university. Most institutions have a dedicated space where employers advertise internships and entry-level or graduate openings through which you can browse and apply for.

It’s important to note that the data science jobs in these 2 types of directories appeal to a huge audience, therefore, they receive a lot of applicants. In other words, the competition is fierce. You would have to really bring your A game in order to stand out. Don’t just send a generic profile as those won’t make it past the first screening at all; tailor your resume toward the specific job. Make sure to emphasize your relevant skills and highlight how they will benefit from hiring you.

Due to the high volume of candidates, however, companies might not even advertise their vacancies on these boards since it’ll be difficult to sort through their applications. So, what’s the alternative?

Data Science Job Boards

Fortunately, with increased demand, comes a variety of solutions. There are many directories out there that cater specifically to those looking for jobs in data:

KDNuggets

KDNuggets is an online platform on all things data science. On top of their extensive blog and online data resources, you’ll also find a page with listings for data science and analysis jobs both in the industry and academia. All openings come from well-known companies and universities, the majority of which are in North America and Europe.

Outer Join

Outer Join is a leading data science job board that offers exclusively remote opportunities from reputable companies for roles in the field such as data engineer, data analyst, ML engineer, etc.

Analytics Vidhya

Analytics Vidhya is by far the largest resource for data science-related positions in India. You have the option to build your own resume directly on the website, as well as take part of hackatons and other exciting events that they offer while you’re on the hunt for your next job.

StatsJobs

StatsJobs offers many job opportunities in the fields of data science and statistics. All the listings come from well-known companies and organizations in different fields like healthcare, finance, academia, and so on. The only snag is that they are primarily in the UK, with few listings for the US, Europe and Asia.

AI Jobs

AI Jobs is exactly what it says on the tin: it boasts jobs in AI, machine learning and data science. You’ll find listings from employers located all over the world, as well as opportunities for remote work.

Open Data Science Job Portal

Open Data Science Job Portal matches your profile with data and ML jobs all over the world. You can apply directly on the website by uploading your resume.

DataJobs

DataJobs is a portal for current open positions in the data world. Unlike other boards we’ve mentioned, you can’t apply directly on the website, so it’s more like a marketplace for job seekers to stay informed and find opportunities in their area.  

These are just some of the job boards we recommend having a look through.

Keep in mind that, even though the vacancies listed are specific to data science, you still absolutely should tailor your data science resume to match the ones you’re applying for. Not only does that show you’re qualified for the position, but it tells your potential employers that you’ve taken the time to study the company and its activities – which is always an advantage.

Company Websites

Nowadays, many companies would advertise their open positions on their own websites. Some of the prominent names include Amazon, Google, Microsoft, IBM, and countless more.

And it’s not just in the tech industry – even publishing giants like Simon & Schuster are looking for data professionals. You just have to have keep checking (or opt in for e-mail alerts whenever a new listing is published).

For even more job opportunities, check out which consulting companies and up-and-coming startups are hiring data scientists.

And if you’ve already found the perfect job posting you want to apply for, but you’re missing a sleek, professional resume, then our 365 Resume Builder is just for you. With this tool, you’ll be able to create your perfect data scientist profile with all the relevant experience to boot.

Freelance as a Data Scientist

Let’s say the traditional 9 to 5 isn’t your thing and you want something more flexible. Or perhaps you’re a data science beginner looking to gain some professional experience. Then, why not try your hand at freelancing?

You can register on different platforms and advertise your services to companies and individuals who are looking for someone to fulfill a one-time or short-term data science task. Such websites include:

Once you have a few projects under your belt, people will find you more trustworthy and begin approaching you for other jobs.

But don’t expect instant results. As the saying goes: Rome wasn’t built in a day.

Network in the Data Science Field

Unlike applying to data science jobs in online directories or accepting one-off projects as a freelancer, this step will not get your foot through the door – at least not directly.

Every career adviser ever will tell you that networking is one of the most important steps. In other words, it’s all about who you know. So, how do you meet people in the industry if you’re just starting out?

LinkedIn

One solution is to approach data professionals directly on LinkedIn. If you see someone who works at a company you admire, shoot them a message and see whether they’d be up for a chat. However, do not harass them with your resume; they won’t be able to get you a job anyway.

Instead, use this opportunity to get to know the person and what they do at work. The goal is to make a genuine connection with someone within the industry. They, in turn, might introduce you to another data scientist and – if you make a good impression – might even put your name forward if an opportunity arises.

E-mail

Firms will often have points of contact for their employees on the official website. Similarly to the LinkedIn example, find someone who works at your ideal position and write them a polite e-mail, explaining your interest in the field.

Again, do not bombard them with requests. If you receive a reply, then it’s a perfect opportunity to strike up a conversation with this person, ask questions, and make a connection. Most likely, they will end up remembering you for your initiative.

Data Science Events and Conferences

Events remain the best way to meet people and make a connection. Whether it’s online or in person, showing your face at multiple events and making people remember you will be beneficial as they will naturally recognize you. Moreover, it’s a great way to strike up a conversation with industry professionals, get the relationship ball rolling, and even offer to keep in touch with them via social media.

We also recommend having something to show. For instance, if you are working on a data science project that you’re really passionate about, don’t hesitate to share with whoever you’re connecting with – this is a great way to demonstrate your skills and even impress potential employers.

A mistake people make is trying to engage with too many people at such events – that way, you only form a shallow connection and risk looking like a brownnoser. Instead, talk to someone longer, ask questions. Even if you end up meeting 2 or 3 people, make sure they leave with a lasting impression of you.

This approach can be expensive, however, which is a big drawback if you’re a job seeker. Some events offer discounts for students or bigger groups that are worth looking into. Or you can always look for volunteering opportunities – this way, you not only get something on your resume, but you get to attend the entire conference for free.

Web pages like KDNuggets Events and SafeGraph are a good resource to keep track of events happening in the near future.

How to Find Great Data Science Jobs: Next Steps

Starting a career in data science is not as daunting as it may appear at first glance. Essentially, being prepared is one of the most important steps you need to take before applying for a job. So, make sure to dedicate some time in perfecting your resume and portfolio. That will help you ace the data science interview as well.

And if you need a boost of knowledge, the 365 Data Science Program is here for you. It offers self-paced courses led by renowned industry experts. Starting from the very basics all the way to advanced specialization, you will learn by doing with a myriad of practical exercises and real-world business cases. If you want to see how the training works, start with a selection of free lessons by signing up below.

Dessie Tsvetkova

Copywriter

Dessie is a Copywriter at 365 Data Science. She holds a Bachelor’s degree in Creative Writing and is currently pursuing a Master’s in Publishing. Her interest in data science is a natural continuation of her coding experience. In her articles, Dessie aims to make breaking into data science simpler and more accessible so that more people can achieve their professional goals.

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