If you are a data scientist, you know that your job revolves around digging through heaps of data to uncover hidden clues, information, and insights. However, condensing plenty of valuable details about yourself into a data scientist resume is a whole new challenge.
When you’re used to working with huge datasets, it can be tricky to go in the opposite direction to try and fit a huge pile of material onto one page.
But fear not! Your profession gives you a solid foundation in data manipulation. With a bit of guidance, a few expert tips, and an example here and there, you’ll learn how to create a stellar data scientist resume that will pass any ATS scan and impress every recruiter.
So let’s get busy turning your document into an attention-grabbing masterpiece!
Key Takeaways
Unless you have decades of experience, your data scientist resume should be one page long.
Take advantage of the chronological resume format to emphasize your latest job and neatly display your career’s progress.
If you lack professional history, you can leverage other activities, such as internships and volunteering, and also make your education section more prominent.
Enrich your resume by writing a position-specific cover letter that features some additional skills and accomplishments you haven’t mentioned in the resume.
What is the Right Format to Use for a Data Scientist Resume?
You’re familiar with the importance of conveying complex information in a clear and concise manner. That’s why you need a strong format for your data scientist resume—to ensure you’ve provided all the crucial information recruiters want to read in an optimal way.
The chronological resume format is by far the most popular. It’s an intuitive, orderly format that emphasizes your latest job and achievements while listing the rest in reverse-chronological order. Its neatness is the main reason why it’s favored by recruiters and easily parsable by the ATS.
In addition to the chronological resume, there are two more formats you can use depending on the circumstances:
The functional resume format, which makes the skills section pop. It is recommended for entry-level candidates who lack work experience but have an impressive skill set. The downside of this format is that it might run into issues with the ATS due to its uncommon formatting.
The combination or hybrid resume format, which has the features of both chronological and functional formats. This format lists notable accomplishments under each skill, which makes it perfect for seasoned veterans or candidates with gaps in employment who have valuable transferable abilities.
Resume Layout
The purpose of a strong resume layout is to make your document readable and your sections visually distinct.
First things first, it’s highly recommended that you fit all of your information onto one page. Many recruiters have to go through countless resumes, and they won’t spend a lot of time examining each one. You want to show them as much as possible, as quickly and clearly as possible, and the following tips can help you achieve that:
Take advantage of bullet points, as they offer the same amount of information as paragraphs while being noticeably shorter.
Pick a clean and professional font that’s easy to read (e.g., Calibri or Arial).
Aim to have a text font size of 10–12 pt, with subheadings being 2–4 pt bigger.
Use a combination of white space and 1-inch margins to define sections and organize them visually.
What Sections Should a Data Scientist Resume Contain?
Let’s talk about the actual contents of your data scientist resume.
Must-Have Sections
The must-have sections it must contain are:
Contact information
Resume objective/summary
Work experience
Education
Skills
Optional Sections
If you have more information to add that can help you increase your chances with recruiters, consider some of the optional sections, such as:
Awards and certifications
Conferences
Hobbies and interests
By the end of this article, you’ll know precisely how to write each of these sections from scratch. Still, wouldn’t you like to speed up the whole process while ensuring a professional and error-free resume as a result? If yes, take a look at our resume builder.
You can start by examining ready-made resumes created by industry experts or downloading PDF samples of these data scientist resumes. When you find the template that suits you, adjust everything from its color to its fonts and sections, and then simply insert your details and download a finished resume!
Data Scientist Resume Template
Name and Surname
Phone number: 000-000-0000 | Email: namesurname@gmail.com | Location: City, State
[Adjective] [your job title] with [years of experience, if applicable] in [your area of expertise, if applicable] looking for a [position] job at [company name]. Eager to apply [relevant skills] gained through [work/volunteer/other experience] to help [company name] [mention what you can do for the company].
Work Experience
Most Recent/Current Job Title Company City, State [Start date] — [End date]
For recent jobs, use 5-6 bullet points to list your top achievements and responsibilities
Use action verbs to make your responsibilities and achievements stand out
Add numbers to quantify your achievements
Previous Job Title Company City, State [Start date] — [End date]
For recent jobs, use 5-6 bullet points to list your top achievements and responsibilities
Use action verbs to make your responsibilities and achievements stand out
Add numbers to quantify your achievements
Oldest Job Title Company City, State [Start date] — [End date]
For older jobs, use 2-3 bullet points to list your top achievements and responsibilities
Use action verbs to make your responsibilities and achievements stand out
Add numbers to quantify your achievements
Education
[Degree] in [Major] [University/college name] [Start date] - [Graduation date]
Skills
Soft Skills
Skill #1
Skill #2
Skill #3
Skill #4
Skill #5
Hard Skills
Skill #1
Skill #2
Skill #3
Skill #4
Skill #5
Additional Sections
Add any relevant additional sections (languages, licenses, publications, hobbies, etc.)
Resume templates
Resume templates that are designed to help you win a jobData Scientist Resume Contact Information
Let’s start our resume with one of the most clear-cut sections—your contact information. You should place the following details in your resume header:
Your name and role
Phone number
Email address
Adding your location is an outdated practice due to security reasons and should only be used if you’re applying for a job abroad. What you can consider adding to your data scientist resume are LinkedIn and Github profiles, for example.
Here’s an example:
Contact Information Example
Susan Jackson
Data Scientist
+ 276 694 7482
susanjackson@example.com
Stuart, VA
linkedin.com/in/susanjackson77
github.com/susan.jackson
Make sure to keep this section spotless—especially your phone number and email address. On a related note, if you’re still using a “witty” email address you made to communicate with friends, it’s probably time to create a new, professional one.
Data Scientist Resume Objective or Summary
Imagine you only had a couple of seconds to introduce yourself to your potential employer. You’d want to start with your strongest skills and most impressive achievements. That’s the goal of a resume summary or objective, and you’ll put one or the other in your resume header next to your contact information, depending on the circumstances.
If you’re a data scientist with plenty of experience, you want to grab the recruiters’ attention with your most prominent professional accomplishments. In that case, you should write a summary and encapsulate your entire resume in 2–4 sentences.
However, if you’re an entry-level data scientist, a resume summary likely won’t do. Since you lack professional history, you should write an objective for your resume to highlight your key skills, motivation, and plans for the future.
Data Scientist Resume Objective
In addition to talking about your outstanding skills in your resume objective, you can include a few more details to spice it up, such as your degree or internship experience.
Here’s an example of how you can write a data scientist resume objective:
Good Example
“Certified data science graduate with a focus on visualization and statistics. Passionate for recommendation engines, customer segmentation, and model productionisation. Leveraged a 1-year internship to refine machine learning skills and knowledge of statistics. Seeking to successfully fill in an entry-level position at [your company] on the road to becoming a competent senior data scientist.”
On the flip side, we have a bland resume objective where a candidate didn’t include anything of value to potential employers:
Bad Example
“New data scientist with no professional experience looking for a job where I can put my skills to use and learn on the go.”
Data Scientist Resume Summary
When writing a data scientist resume summary, your goal is to condense your entire career into one or two remarkable achievements. Make sure to mention your experience and some skills that can separate you from less competent candidates.
Here’s a good example:
Good Example
“Analytical data scientist with 7+ years of experience in the field. Proficient in Python (including Scikit-learn, Flask, and NumPy), along with machine learning algorithms and deep learning techniques. Notable achievements include realizing $500K in incremental annual revenue for [previous company] by building and implementing a production recommendation solution.”
This resume summary is brimming with valuable skills and impressive accomplishments. Now compare it to the following poorly-written example that falls short in those aspects:
Bad Example
“Accomplished data scientist with plenty of experience looking to join a big company and help them optimize their businesses.”
Data Scientist Resume Work Experience
As it’s usually the most important section, the previous work experience information is what recruiters will pay attention to first when looking at your data scientist resume.
General Tips
For starters, there’s a clear formula to follow when adding your past jobs to your resume. It goes as follows:
Your role
The company and its location
Duration of employment
Bullet points with your achievements and results obtained
You want to make the most out of your bullet list, which is why you shouldn’t list just any task or responsibility. Instead, you should have 3–5 bullet points for each previous job that demonstrate something impressive.
Think of the times you exceeded expectations, KPIs, or benchmarks. Use numbers, percentages, and statistics to quantify the results obtained and make them more concrete in the eyes of recruiters.
Moreover, try to work in some catchy and memorable action verbs and power words. Terms like “diagnosed,” “enhanced,” “executed,” and “implemented” stand out and are bound to make your accomplishments notable.
Data Scientist With No Experience
Even if you don’t have a professional history in the field of data science, you can still make an irresistible work experience section. The only difference is that you’ll be using substitute endeavors, such as internships, freelance work, volunteer experience, and even college projects.
Here’s how a candidate leveraged their internship to create a remarkable work experience section:
Data Scientist Intern
Work Experience
Data Scientist Intern
SolutionTech
Seattle, WA
May 2022–December 2022
Utilized Python to build machine learning models that predict customer churn, achieving an 87% accuracy rate.
Conducted A/B website layout and content testing to implement changes that resulted in an 11% traffic increase and a 5% conversion rate boost.
Developed a new product recommendation system in collaboration with cross-functional teams to increase the average order value per customer by 13%.
Experienced Data Scientist
A senior data scientist resume should show what results all those years of experience have brought. As much as two-thirds of your resume can be dedicated to this section if you have multiple jobs to list in reverse-chronological order.
When including your achievements, focus on those that show how your employers benefited from your extraordinary abilities.
Let’s see that in an example:
Senior Data Analyst
Work Experience
Senior Data Scientist
Novitec
Brooklyn, NY
July 2018–Current
Utilized machine learning algorithms to create an automated fraud detection system, reducing fraudulent transactions by 75% and saving the company $4.5 million annually.
Spearheaded the development of a personalized recommendation engine using deep learning to boost customer retention by 17% and increase the average order value by 27%.
Trained and mentored up to 7 junior data scientists and engineers per year, which led to faster skill development and an overall boost to the company’s productivity.
Data Science Manager
When you’re applying for a position of a data science manager, demonstrating your leadership and management skills becomes just as important as showcasing your prowess in data science itself. Therefore, you shouldn’t forget to put the results front and center to show the impact that your competence had.
Here’s a good example:
Data Science Manager
Work Experience
Data Science Manager
EnergoChem
Pittsburgh, PA
October 2020–Current
Led a team of 9 data scientists and analysts to devise and implement a data-driven marketing model, resulting in a 25% increase in the company’s revenue.
Spearheaded a project to develop a customer churn model, using prediction algorithms to reduce customer churn by 19%, saving the company more than $650,000 in revenue.
Developed a targeted marketing campaign in collaboration with the marketing and design teams, boosting specific product line sales by up to 33%.
Data Scientist Resume Education Section
The education section is another straightforward one with a simple format to follow. It goes like this:
Your degree
University name
First and last year of attendance
(Optional) High GPA, courses, extracurricular activities, projects, etc.
You should include the optional bits as bullet points if you have little to no professional history. Otherwise, it’s better to keep this section brief and let your work experience do its thing.
Another thing you can do is include a degree, even if you’re still a student at the time of applying for a job. In that case, you can either put an expected graduation date and mark it as such or place “current” instead.
Now let’s take a look at the example:
Education Section Example
Education
Bachelor of Science in Mathematics and Economics
University of Delaware, Newark, DE
2016–2020
GPA: 3.75
Relevant Courses: Statistics and Probability, Machine Learning, Data Visualization, Big Data Analytics, Optimization Techniques
Data Scientist Resume Skills
How do you differentiate yourself in the sea of other data scientist candidates who have similar skills to yours? The answer is twofold—by:
Adding relevant skills to your data scientist resume
Proving them
Start by doing the research. You’ll find out what types of skills recruiters are looking for by carefully reading the job advertisement and researching the company. Once you do it, you can simply create a list of skills that will go right after your education section.
Keep in mind that the main focus of this part of your resume should be on your job-specific, hard skills. Only after including them should you include a shorter selection of soft skills. It’s also important not to mix these two lists together, as they are fundamentally different.
When it comes to proving your skill set, the best way to do it is through your work experience. Try to put relevant skills next to the work accomplishments you mentioned to show how your abilities helped you obtain specific results. This way, you’re not just making vague claims that you possess certain abilities—you’re giving actual proof.
Hard Skills
Some of the hard skills you can add to your resume are:
Data analysis
Data visualization
Mathematics
Programming
Machine learning
Statistics
Probability
Quantitative analysis
Modeling
Technical Skills
Within hard skills, you can also list highly specialized technical skills, such as:
Python
NoSQL
R
Hadoop
Cloudera
Perl
Soft Skills
Recruiters always look for candidates with some of these soft skills:
Creativity
Critical thinking
Communication
Collaboration
Problem-solving
Time management
Research
Data Scientist Resume Optional Sections
Finally, you can give your resume an extra punch with some of the following optional sections:
Awards & Certifications
Awards and certifications can be vital in the field of data science because they demonstrate both high levels of expertise and commitment to the profession. Listing them on a resume is one of the easiest ways to stand out among the competition.
It’s also common practice to include your awards and certifications in reverse-chronological order, focusing on the latest first. However, make sure to only list those that are relevant to the position that you’re applying for.
Furthermore, you should mention some relevant details, such as the name of the certification or award, the organization that granted it, and the date when it was obtained. You can also briefly mention what the certification signifies—any particular skill or knowledge area covered—or what the award was for.
Now let’s put all that into practice and see an example:
Certifications & Awards
Certifications
Certified Data Scientist, IBM (2020)
AWS Certified Big Data - Specialty, Amazon Web Services (2019)
Awards
Best Paper Award, International Conference on Machine Learning (ICML) (2018)
Young Investigator Award, ISSNAF (2016)
Conferences
Conferences represent opportunities for individuals to learn, share their knowledge, and network with other professionals. Therefore, listing them in your data science resume shows dedication and engagement with the community. It’s particularly important to list those conferences where you gave speeches, held presentations, or participated in workshops.
Conferences & Presentations
Conferences
International Conference on Machine Learning (ICML), Long Beach Convention & Entertainment Center, Long Beach, CA (2019)
International Conference on Data Mining (ICDM), Los Angeles, California (2018)
Presentations:
A Deep Learning Approach for Time Series Forecasting, ICML (2020)
Hobbies & Interests
By mentioning your hobbies and interests, you help recruiters paint a complete picture of who you are as a person beyond your skills and expertise in data science. This section can also differentiate you from other candidates and help you grab recruiters’ attention more easily. Moreover, you can create a personal connection with recruiters and hiring managers by finding common interests.
A great thing about your hobbies and interests is that they don’t have to be related to your profession at all. This is one of the sections where you get to be the real you. If you display a genuine passion for something, it won’t go unnoticed.
On a final note, certain hobbies and interests might imply important qualities about you, such as creativity, curiosity, and problem-solving.
Should You Submit a Cover Letter With Your Data Scientist Resume?
Cover letter templates
Create a cover letter by filling in a free template and sharing it for freeRemember how we mentioned that your resume should be one page long? A cover letter is a perfect opportunity to talk more about your skills and experiences without breaking that rule.
Not only that, but you show commitment and hardworking tendencies by going above and beyond to submit a document that many consider optional and don’t write.
Expert Tips for Creating a Data Scientist Resume
These expert tips will help you craft a top-notch resume:
You should make all the links (including your email address) in the contact information section of the soft copy of your resume clickable. It shows your attention to detail and makes it much easier for recruiters to check them out.
PDF is one of the best file types when you’re submitting a soft copy of your data scientist resume, as it preserves layout and formatting across various devices. Still, you should check the job ad to make sure they are accepting PDFs in the first place.
If you find out who the recruiter is, you can address them personally in your cover letter to build rapport.
Avoid adding personal pronouns to your objective or summary—you should show what you bring to the company that you’re applying to.
While soft skills are important to recruiters, they shouldn’t overshadow your hard, technical skills since these are mandatory for the job. Moreover, soft skills are much harder to prove. For all these reasons, you shouldn’t go overboard and list dozens of them but only include a select few.
Don’t underestimate the power of the hobbies and interests section. One of their perks is that they are great conversation starters during interviews.
Before we wrap things up, here are some examples of professional data scientist resumes you can use for research and inspiration.
Frequently Asked Questions About Data Scientist Resumes
#1. What should a data scientist put on a resume?
The most important things for data scientists to put on a resume are their work experience, education, and skills. Additionally, they should also include their contact details and a brief introductory paragraph in the form of a resume summary or objective. Finally, they can insert some optional parts, such as certifications, awards, conferences, and more.
#2. What is the best resume format for a data scientist?
In most cases, the best resume format for a data scientist is the chronological resume format. Recruiters are mostly familiar with it and know how to quickly extract a lot of information from such resumes, even by just skimming them for a few seconds. Furthermore, this format is optimized to work well with any type of resume-parsing software.
#3. How do you write an entry-level data scientist resume?
An entry-level data scientist can make up for a potential lack of professional history by writing about their internships, volunteer work, school projects, and similar activities. Additionally, they can emphasize their education section and go in-depth about their academic accomplishments, such as relevant courses, notable achievements, a high GPA, extracurricular activities, clubs, etc.
#4. What skills do data scientists need?
Data scientists often need to have complex skill sets that include many hard and technical skills. Depending on the position you’re applying for, you should mention anything from statistical analysis and computing, machine learning, and deep learning to mathematics and programming on your resume.
Additionally, recruiters often look for candidates with prominent soft skills, such as critical thinking, communication, and problem-solving.
#5. How long should a data scientist resume be?
A data scientist resume should generally be one page long. If you have many years of experience and an extraordinary amount of notable accomplishments to showcase, you can write a two- or even three-page resume. However, the vast majority of candidates should try to fit everything onto one page by being brief and concise and using powerful tools like bullet lists.
Closing Thoughts
Hopefully, writing a catchy and professional data scientist resume doesn’t seem so daunting anymore. You start by following the rules and guidelines closely, and then you can spice things up with a couple of personal touches here and there.
After all, as a data scientist, you’re well aware of the importance of numbers, but you also know that they usually don’t tell the whole story. That’s why it’s crucial to let a bit of your bright and brilliant self through. That way, you’ll be on the road to landing your dream job in no time!