Why You Aren’t Getting Hired as a Data Science in 2025

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There was a time when data science and technology recruitment companies were thriving. However, over the years the recruitment process has changed so much that it not only made it harder to find the right talent but companies are also putting up barriers that make it harder to recruit the right person.

Although you are constantly seeing data professional job vacancies opened up on LinkedIn, the sad truth is that some of these are fake. Some organisations are posting jobs to get recognition, whilst others have jobs posted just to make candidates go through hoops only to be told no.

With this in mind, is data science still a solid go-to career choice moving forward? Over the years the data science market has been booming due to the value of data and businesses wanting to extract as many insights from it as possible. However, in 2025, a lot of you who are considering a career in data science may still be wondering if it’s the right choice to make. Further, for those who are already qualified and job-searching, what are the reasons why they aren't getting hired?

There are 2 angles from which we will be looking at the job market today: Is data science still a good career choice? And why are you not getting hired as a data scientist?

Let's first jump in and see why those who are currently looking are not getting hired and then turn our attention to those wondering about the future of data science.

Why You Aren't Getting Hired

Your Resume

The sad truth is that a lot of people put a lot of effort into their resumes. If this is you, and you aren't getting the attention you feel your skill set and experience deserve, perhaps you are falling victim to this: a lot of great talent gets hidden behind poorly structured resumes.

The first thing first is clutter. Although you may feel like you need to cover up all the white space possible, sometimes or more time recruiters want to see white space. You want to mention the important things you have done and that can be highlighted in a few words, not paragraphs and paragraphs.

Language is also important. Your choice of language will get you sussed out very quickly. For example, someone who has been riding the buzzword wave their entire career may start to find that these once-useful catch phrases no longer pull their weight, even with the use of fancy verbiage and intricate sentence structuring.

Long story short: A lot of words don’t always necessarily tell a great story. Here are some other common resume mistakes to avoid.

More to Life Than Work?

Although some employers don’t want to hear that there is more to life outside of work, the reality is that there is. And what you do outside of work will determine your personality and character and if you would genuinely be a good character fit for the company.

However, a lot of recruiters and employers want to know your job doesn’t stop at 5 pm. For example, I have been a technical writer and content creator around the machine learning and artificial intelligence space for 4+ years now. However, outside of my 9-5, I write on Medium and — though it began with technical content — I started to go into other niches to explore my writing skills and how I can adapt to different audiences.

Let’s take a software developer for example, what are you doing to position yourself in the community or other aspects of self-development? Are you attending talks? Are you part of a community? Are you taking on speaking opportunities?

The sad truth is that recruiters do not care if you run yearly marathons or if you know how to crochet. Although it shows your characters, the chances of you getting an interview based on them are slim to none. You’re not applying for college, you’re trying to build yourself a career.

Prep So You Don’t Fail

You would easily believe that candidates regularly prepare for jobs that they apply for, but it is shockingly surprising how many people think that they can just wing it. The digital life we live in makes it much harder when you’re competing with 500+ applicants for your dream job. So, if you want it, make sure your application sticks.

Going back to your resume: not only do you need to ensure that your resume is simple and effective, but also that it tailors to the job that you are applying for. You also need to consider the company itself. You want to find these connection points and make sure they’re stated on your resume so that you stand out.

Give Answers That Have Value

Rather than sitting and struggling with answers that won’t have value to interview questions, prepare for this inevitably and say something that will intrigue your recruiter. The biggest mistake you can make is insulting them by spouting off useless answers, being unprepared, and wasting their time; they can see right through it.

Give them straightforward answers because that is what they want. They don’t want to have to ask you multiple questions before they are able to finesse the answer they actually want. Giving an answer — any response that has value, even if not the perfect answer — shows that you are confident in yourself and the right person for the role.

A reminder: people on the other side of the table hiring you aren’t so different and want exactly what we would want.

Data Science CareerProspects in 2025

 
Now let's move on from the individual question of "why am I not getting hired as a data scientist right now?" and focus on something more broad: "will anyone be getting hired as a data scientist in the future?" Let's have a look at some factors that will impact the continued success of the data science field and your place in it.

Is Data Science Still Sexy?

Your choice of wanting to start a data science career is completely up to you. There is nobody else that can make that decision but yourself. You want to analyse the requirements for becoming a data scientist and reflect on your abilities to achieve these requirements and skills.

However, if you worry that data science is dying, I am here to tell you that it is not. Data science is set to remain a good career choice for the year 2025 and beyond. Understanding the choice of a new career consists of taking into consideration the security around the role and its relevance in the next 5-10 years. Although generative AI tools are dominating the market, in the next 5-10 years alone they will not solely be left to their own devices and will still need human intervention.

Do Your Interests Align?

There are three things you need to be interested in when taking on a data science career: coding, maths and statistics. If these are not of interest to you, then you should not be considering a career in data science. I’m not saying you have to be an expert in these areas, you need to have a simple interest which will drive your data science career.

Let’s start with coding. In the data science sector, one of the most popular languages you NEED to learn is Python. It is one of the easiest programming languages to learn and many data scientists use this as their main programming language. One way of testing your interest is doing short Python courses and seeing if you resonate with them. If you do, there is an interest there and you can continue to develop your Python skills.

Now, maths and statistics go hand-in-hand. You will need to use maths and statistics to analyse your data and find valuable insights to show to stakeholders. If you do not have an interest in these, you will fail to become a successful data scientist. A lot of people forget that maths and statistics are the foundations of data science and that it will help you learn as well as your ability to put the pieces of the puzzle together.

If you are interested in a data science learning roadmap, check out A Free Data Science Learning Roadmap: For All Levels with IBM

Data Science Job Opportunities

Once you complete your data science learning roadmap and have created a portfolio of projects, the next thing you want to do is start your job-hunting process. he first section of this article covered why you might NOT be getting hired, but let's look at more productive recommendations here.

DO PROJECTS! You need to showcase your learnt skills to your next employer and the best way to do this is by projects. Another reason why this is important is that some organisations may still be looking to hire professionals with traditional educational backgrounds such as a degree. However, if you can showcase your skills and prove that you have the same knowledge as somebody who went to university for 4 years, you may have a higher chance of landing a job.

Your choice of job depends on various factors, such as location, company, salary, etc. A lot of data science roles still remain WFH jobs, making it easier for more and more people around the world to access these roles from the comfort of their homes.

According to Glassdoor, the average data scientist salary is USD 117K/yr Average base pay, with a range from USD 95K - USD 145K/yr. As of January 2nd 2025, there are 1,025 results for data science roles in the UK and 4,641 in the United States.

Wrapping Up

 
If you enjoy learning data science and have an interest in the typical day-to-day responsibilities of a data scientist, then a career in data science may be for you. The only way you will know this is by learning the fundamentals and putting your skills into practice with real-life projects. Data science is not a dying career; however, make sure it is a good career choice for you before you enter it.

Also keep in mind some of the hard truths covered in this article: if you’re looking for a new role in 2025, take the pointers in the Why You Aren't Getting Hired section to heart, as they can be the difference between you getting your dream job and having to keep looking.

Good luck out there!
 
 

Nisha Arya is a data scientist, freelance technical writer, and an editor and community manager for KDnuggets. She is particularly interested in providing data science career advice or tutorials and theory-based knowledge around data science. Nisha covers a wide range of topics and wishes to explore the different ways artificial intelligence can benefit the longevity of human life. A keen learner, Nisha seeks to broaden her tech knowledge and writing skills, while helping guide others.