If you’re wondering why become a data scientist, there are many reasons to choose this career field. But how can one land a job, whether with or without actual work experience?
Becoming a data scientist isn’t that hard. All you need is to have the right data scientist skills that employers are seeking and craft a winning resume that would highlight those skills, as well as your accomplishments.
In this guide, we will share with you the top skills required for a data scientist and tell you how to put them on a resume the right way to win the job!
But before you go all-in what data scientist skills are, the first step might be to read about jobs of the future 2025-2035.
What Is Data Scientist?
So, you’ve decided that you want to work as a data scientist make a first step and find a matching data scientist resume sample. Before you make up your mind and start learning data scientist technical skills, let’s define what do data scientists do?
In a nutshell, data scientists are analysts who are dealing with data. Individuals who occupy such positions are responsible for collecting large amounts of data (both structured and unstructured) and then analyzing, processing, managing, and interpreting it.
Now, let’s move on to defining the must-have skills and looking for ways to use your skills and experiences during the job search process to engage hiring managers and get more interviews.
Data Scientist Technical Skills
Today, being a data scientist is a dream job for many people. Such jobs offer a high salary, the demand for specialists grows rapidly, and there is plenty of space for professional growth. And this is just a part of a reason.
But, what are the key skills you need to possess? The main technical skills for data scientist that are in demand today (and will likely be in demand in the future) include
- computer science;
- SQL database;
- Hadoop platform;
- Apache Spark
- unstructured data;
- machine learning and AI;
- data visualization;
- automation tools;
- data wrangling;
- linear algebra & multivariable calculus.
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Data Scientist Non-Technical Skills
To make your job application shine, apart from the hard and technical skills, you should specify at least a few soft skills. In case you aren’t sure what those are, soft skills are non-specialized skills that relate to your personality. These characteristics help employers define how successfully you can participate in the work process.
If you really want to attract the recruiter’s attention and land an interview, here is a list of the key data scientist non technical skills you can include in your resume:
- interpersonal skills;
- creative thinking;
- critical thinking;
- active learning’
- generating hypotheses.
Top Skills of Data Scientist to Be an In-Demand Applicant for the Job
The skills of a data scientist are very diversified. To fill this position, recruiters are looking for job seekers that have a good combination of hard, job-related skills, as well as a number of soft skills.
Earlier, we’ve already named quite a few skills (both soft and hard). However, how to know which ones your potential employer demands the most? Here are the top data scientist skills you will need to get employed:
- data analysis;
- active learning.
Now, let’s take a closer look at each of these top skills that all recruiting firms are looking for in applications.
Pretty much all roles in data science imply that you will be expected to use certain tools of the trade. That is why having at least basic programming skills is one of the core requirements. To succeed in this role, specialists should be well familiar with and know at least one database querying language (SQL) and a statistical programming language (for example, Python or R).
Hadoop is one of the handiest tools for data scientists when they encounter large volumes of data. This one may not necessarily be listed in the job description and requirements, but many employers heavily prefer the knowledge of Hadoop. According to a study, almost 3,500 data science jobs posted on LinkedIn rank Hadoop as the second most important skill they are looking for. Thus, having this skill can give you a competitive advantage.
This one should go without saying. Data scientists are pretty much analytical experts whose task is to collect, manage, and analyze large volumes of data, both raw and structured. Therefore, one of the vital data scientist skills is data analysis. This skill isn’t always specified directly in the job requirements, but that’s because it comes without saying. So, if you still lack this skill, you really should work on it.
Throughout the past decade, companies of all sizes and niches have been strongly encouraging teamwork between their specialists, teams, and departments. Thus, teamwork became one of the core soft skills for all types of jobs.
As a data scientist, you will be expected to be great in collaboration. Most likely, you will have to work together with the company executives, product managers, designers, marketers, and other specialists to improve workflow and reach better results.
This in-demand skill plays a huge role in your overall success in the data scientist position. This is because, just like many other tech-related fields, data science is changing rapidly. To stay competitive, you have to be able to keep up with these changes. Thus, employers are seeking active learners who will be able to recognize innovation and adapt to it quickly and efficiently.
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How to Improve Data Scientist Skills
Now that you know about the key skills required for a data scientist, you are probably wondering how to fill in the gaps. We recommend that you invest in your career and capture the opportunities for mastering the top skills. And we will share some of these opportunities with you.
Opt for an Online Degree
To ensure that your knowledge and skills match the job duties of the data scientist, you need to have relevant education. A high school diploma is not enough to apply for such occupations. Thus, it’s vital to undertake additional training.
Luckily, this doesn’t mean you need to go back to college. In fact, various online degree programs and courses for data scientists will give you all the same benefits.
Follow Influencers in the Field
Although taking a course is a more obvious way to acquire the necessary data science skills, self-learning is also an option. The Internet is full of helpful resources that can help you learn anything, and data science is not an exception.
If you do a bit of research, you can find tons of quality career resources, including online communities, forums, lectures, and, of course, blogs and influencers. Keeping an eye on trusted influencers and blogs, you can be in the swim.
If you are looking for a helpful data scientist blog, here are our top five picks:
- Data Science Central;
- SmartData Collective;
- What’s The Big Data?;
- Kaggle Blog;
As a bonus, here are also the top five data science experts to follow on Twitter:
- Wes McKinney;
- Yann LeCun;
- Dean Abbott;
- Kirk Borne;
- Mike Tamir.
Feel free to follow these influencers and blogs to stay updated on industry news and trends.
Network Like a Pro
Networking is another time-tested way to acquire the needed data scientist skills. Building your own network of like-minded specialists is a great opportunity for exchanging knowledge and experience.
How do you create a network? The easiest way to get started is to attend different relevant events and make new acquaintances.
Data Scientist in the Workplace
Typically, data scientists are working in the office environment to communicate with other specialists effectively . However, it’s also possible to find an online job.
The basic data scientist job requirements include
- BA in a relevant field;
- proven experience;
- knowledge of coding;
- understanding of machine learning;
- business acumen.
How to Showcase Your Skills
After you obtain the required education and data scientist skills, there is just one more thing you need to enter the job market - a bot-beating resume. And to make one, you should know how to put those skills on a resume to boost your chances and stand out from other applicants.
Skills for Resume [Example]
All your data scientist skills should be listed in bullet points in a separate section on your resume.
Here is how this part of your resume should look like:
Data Science Skills
- Hadoop Platform
- Data Analysis
- Data Visualization
- Critical Thinking
As you can see, it’s not hard to put your skills on a resume. However, there are a few handy tips you should keep in mind:
- combine hard and soft skills;
- don’t make the list of skills too long;
- tailor your skills section to the data scientist requirements;
- don’t stop there - highlight your best skills in other sections of your resume.
Skills for the Job Interview
Having all the skills needed to be a data scientist and listing them on your resume should help you get an interview invitation. But your work doesn’t stop there. An interview is another chance to impress the recruiter and prove that the company should employ you. So, you should do your best to showcase your skills during the interview.
Here are a few tips to help you prove your skills:
- mention your skills;
- use insider language;
- ask questions;
- show your confidence.
Pro Tip: To make it really successful, be sure you prepare for your interview and possible questions in advance.
Sample for Data Scientist Resume Skills section
The skills and experience sections of your resume can either help you get noticed by an applicant tracking system and outdo ATS bots or fail. Let’s see two examples of how to make these sections match the data science requirements and ensure success.
Data Scientist Skills in a Resume Skills Section
For the skills section, study the job description and list your key matching skills in a bulleted list.
Here is a sample resume skills section:
Data Scientist Skills
- Python Coding
- SQL Database
- Excellent written and verbal communication
- Machine Learning
- Critical Thinking
- Hadoop Platform
- Problem Solving
- Data Analysis
- Data Visualization
Data Scientist Skills in a Resume Work Experience Section
Highlight your top skills for data scientist in the work experience section using action verbs, keywords, and rough numbers.
- Fulfilled all data science tasks for a leading company.
- Helped the company generate 15% higher revenue by introducing more effective models for analyzing and predicting market trends.
- Reached 25% higher accuracy in predicting stock price.
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To Wrap It Up
Becoming a top-level specialist requires you to have a solid data scientist skills set that should include hard and soft skills. Hopefully, after reading this article, you have a clearer idea of what the skills needed for data scientist job are and know which direction you should be heading to land your dream job.
Following the tips from this guide, you should be able to showcase your data scientist qualification on a resume in the most effective and engaging way. If you are still not sure how to create a job-winning resume, feel free to get professional help from the SkillHub team, and we’ll help you reach your goal!