You’re a data scientist. You solve complex problems.
Your newest problem: writing a resume for that elusive data scientist role.
Fortunately, you’ve arrived at the best place. This guide will take you through a range of steps, so you can create a data scientist resume that gets results.
Specifically, we will cover:
- An example of a finished data scientist resume that works
- How to write a data scientist resume that’ll fill up your interview diary
- How to make your data scientist resume stand out [with top tips & tricks]
Before we get stuck into the data, here’s a data scientist resume example, created with our very own online resume builder:
This resume performs as well as it looks. Just follow the steps in this guide to create a data scientist resume that gets great results, just like the above example.
Besides our data scientist resume example, we've got even more resume examples for professionals in the computer science field:
- Data Analyst Resume
- Data Entry Resume
- Computer Science Resume
- Artificial Intelligence Engineer Resume
- Engineering Resume
- IT Resume
- Software Engineer Resume
- Web Developer Resume
- Java Developer Resume
How to Format a Data Scientist Resume
Before you can reveal why you’re the best person for the job, you need to pick the best format.
Now, this is more important than it sounds.
It will allow your best attributes to ‘jump off the page’ into the recruiters' vision.
The most common resume format is “reverse-chronological”, and it’s for good reason. Essentially, it allows the recruiter to immediately see the value that you provide. We recommend the majority of individuals start with this format.
The following resume formats also get our approval:
- Functional Resume – If you have strong skills, but a weak work history, then this resume format is recommended. It’s ideal for skilled scientists that don’t have a lot of experience or have gaps in their employment history
- Combination Resume – Acting as a combination of both the “Functional” and “Reverse-Chronological” formats, you can use a combination resume if you have a wealth of work experience
Once you’ve chosen your format, you need to organize your resume layout.
Use a Data Scientist Resume Template
As a data scientist, you present data in a structured way.
The same needs to happen to your resume.
However, creating a structured file isn’t an easy task!
You could use Word, but then you will have to risk the layout falling apart with every small alternation.
Want to skip formatting issues? Use a data scientist resume template.
What to Include in a Data Scientist Resume
The main sections in a data scientist resume are:
- Work Experience
- Contact Information
- Skills
- Education
Want to go a step further? You can also add these optional sections:
- Awards & Certification
- Projects
- Languages
- Interests & Hobbies
But wait –
What should you write for each section?
Read on to learn how.
Want to know more about resume sections? View our guide on What to Put on a Resume.
How to Correctly Display your Contact Information
Now, there is no need to get creative in this section.
The only requirement is accuracy.
An incorrect contact section may mean the recruiter can’t contact you – disaster!
The contact information section on your resume must include:
- Full Name
- Title – In this case, “Data Scientist”
- Phone Number – Check this multiple times for errors
- Email Address – Use a professional email address (firstname.lastname@gmail.com), not your childhood email (elliebelly123@gmail.com).
- (Optional) Location - Applying for a job abroad? Mention your location.
Correct Example:
- Ellie Branning, Data Scientist. 101-358-6095. ebranning@gmail.com
Incorrect Example:
- Ellie Branning, Data Scientist Whizz. 101-358-6095. elliebelly123@gmail.com
How to Write a Data Scientist Resume Summary or Objective
It’s safe to say that recruiter’s don’t have time to dig into the data of every resume.
Instead, they scan the resume for the main points.
In fact, studies have shown that recruiters spend just a few seconds on each resume!
So, what can you do?
You need an introduction that makes your value ‘jump off the page’.
To do this, use a resume summary or objective.
These are snappy paragraphs that go on top of your resume, just under your contact information.
Now, this section is extremely important. This small paragraph could be the deciding factor between scoring an interview and simply having your resume dismissed.
But what is the difference between the two sections?
A resume summary is a 2-4 sentence summary of your professional experiences and achievements.
Data Scientist Resume Summary Example
Certified data scientist with 12 years of experience for a diverse clientele. Achievements include updating data streaming processes for an 18% reduction in redundancy, as well as improving the accuracy of predicted prices by 18%. Highly-skilled in data visualization, machine learning, leadership.
A resume objective is a 2-4 sentence snapshot of what you want to achieve professionally.
Data Scientist Resume Objective Example
Motivated data scientist with 2+ years of experience as a freelance data scientist. Passionate about building models that fix problems. Relevant skills include machine learning, problem solving, programming, and creative thinking.
So, which one is best, summary or objective?
Generally, we recommend that experienced data scientists go with a resume summary. Those who are new to the field, like graduates and career changers, would be better suited to an objective.
How to Make Your Data Scientist Work Experience Stand Out
Recruiters need to be confident that you will do a good job for the company.
Listing your work experience is the easiest and best way to do this.
Here’s the best way to structure your work experience section:
- Position name
- Company Name
- Dates
- Responsibilities & Achievements
Here’s an example:
Data ScientistHedge X03/2016 - 05/2019- Improved the accuracy of predicted prices by 18%.
- Coordinated a team of 16 data scientists working on 4 different projects.
- Updated data streaming processes for a 18% reduction in redundancy.
To separate your resume from the other applicants, you should talk about your best achievements, not your daily tasks. Doing so will clearly show how you can benefit the company.
Instead of saying:
“Data streaming.”
Say:
“Updated data streaming processes for an 18% reduction in redundancy.”
As you can see, the first statement doesn’t effectively convey your achievements. It shows that you streamed data, but it doesn’t show the results of your work.
The second statement shows that you managed to reduce the redundancy numbers. Hard numbers that prove your skills – can’t argue with that!
What if You Don’t Have Work Experience?
Maybe you’re trying to break into the data science field?
Or maybe, you have already worked in the industry, but never in this specific role?
Your experience is null.
A recruiter will want data scientists that they can rely on. Whether you have job experience or not, being able to show that you have the skills is the most important factor.
If you already have proof of your data science skills, feel free to link to them in your resume.
With that said, there is still time to create a portfolio.
Here are several ways you can show your talents (and even get paid for it):
- Start freelancing.
- Offer your skills to friends and family.
- Contribute to open source projects on GitHub.
- If the above doesn’t work, become your own client! Show your skills by creating mock projects.
Are you recent data scientist graduate? Make sure to check out our student resume guide!
Use Action Words to Make Your Data Scientist Resume POP!
- “Made”
- “Worked”
…are all common words that the recruiter sees time and time again.
However, you want to separate your resume from the competition, which means using power words to make your achievements stand out:
- Conceptualized
- Determined
- Formulated
- Initiated
- Managed
- Spearheaded
How to Correctly List your Education
Every great resume needs an education section.
But don’t worry, there is nothing too complicated here.
Simply enter your education history in the follow format:
- Degree Type & Major
- University Name
- Years Studied
- GPA, Honours, Courses, and anything else you might want to add
Here’s what it should look like:
BSc in StatisticsUniversity of Bath2012 - 2016- Relevant Courses: Probability and Statistics, Generalised Linear Models, Applied Statistics
- GPA: 3.8
Now, you may have some questions on this section. If so, here are the answers to some of the most frequent questions that we get:
- What if I haven’t finished education yet?
Regardless of whether you’re a data science graduate or still studying, you should mention all years studied to date
- Should I include my high school education?
The general rule is to only include your highest form of education. So, include your high school education if you don’t have a relevant degree for data science
- What do I put first, my education or experience?
Experiences are the priority, so those go first. If you’re a recent graduate, you will likely need to start with education.
Need to know more? Check out our guide on how to list education on a resume.
Top 15 Skills for a Data Scientist Resume
When it comes to the skills section, the hiring manager has seen it all before.
In fact, they need a data scientist to help with the entire pile of data scientist resumes!
You see, everyone lists all of their skills, even those that related to the job.
Your skill section should highlight your top skills in a way that is specific to the role.
Here are some of the most common data scientist skills:
Hard Skills for a Data Scientist Resume:
- Data Analysis
- Statistics
- Data Visualization
- Quantitative Analysis
- Machine Learning
- Modelling
- Mathematics
- Probability
- Debugging
- Programming
Soft Skills for a Data Scientist Resume:
- Critical Thinking
- Communication
- Research
- Time-Management
- Collaboration
Pro Tip:
- Data scientists frequently use tools, such as Cloudera, PERL, and OpenRefine. If there are any tools or pieces of software that you’re an expert in, include them in your skills section.
Here’s a more comprehensive list of 101+ must-have skills this year.
What Else Can You Include in a Data Scientist Resume?
We’ve now covered every essential resume section.
However –
Is it the absolute BEST it can be?
Doing a great job with the above sections should be enough to get you shortlisted, but adding a few of the following sections could be the major factor in whether you become their new data scientist or not.
Awards & Certifications
Have you won an award for your work in a field that relates to data science?
Have you completed any courses to improve your skills and knowledge?
If you said yes to any of the above, make sure to mention them in your resume!
Don’t worry if you don’t have any awards or certificates, there a few companies that allow users to do online certifications, like Google.
Awards & Certificates:
- “IBM Data Science” - Coursera Certificate
- Google Certified Professional Data Engineer – GCP
- Microsoft Professional Program Certificate in Data Science
- “Deep Learning” - Coursera Certificate
- “Critical Thinking Masterclass” - MadeUpUniversity
Languages
Even though it is very unlikely to need a second language, you may want to add a small languages section to your resume.
You see, being able to speak a second language is always an impressive skill to a hiring manager.
Rank the languages by proficiency:
- Native
- Fluent
- Proficient
- Intermediate
- Basic
Interests & Hobbies
Now, you may be wondering, “why would a recruiter need to know about my love for kayaking?”
Well, your hobbies reveal more about who you are as a person.
A hobbies section is an easy way to add personality to your resume, so add one if you have the space.
Here’s which hobbies & interests you may want to mention.
Include a Cover Letter with Your Resume
Here the thing –
Cover letters still play an important role during the application process.
They provide a number of benefits, but the main reason for using a cover letter is to show the recruiter that you care about working for their company.
To create a winning cover letter, we must use the correct structure.
Here’s what we recommend:
You should complete the following sections:
Personal Contact Information
Your full name, profession, email, phone number, location, and website (or Behance / Dribble).
Hiring Manager’s Contact Information
Full name, position, location, email.
Opening Paragraph
It’s no secret that hiring managers skim through resumes and cover letters. As such, you need to hook the reader within the first few sentences. Use concise language to mention:
- The position you’re applying for
- Your experience summary and best achievement to date
The Body
Once you’ve sparked the reader’s interest, you can get deeper into the following specifics:
- Why you chose this specific company
- What you already know about the company
- How your skills relevant for the role
- Which similar industries or positions have you worked in before
Closing Paragraph
Don’t just end the conversation abruptly, you should:
- Conclude the points made in the body paragraph
- Thank the hiring manager for the opportunity
- Finish with a call to action. This is a good way to start a conversation. A simple “At your earliest opportunity, I’d love to discuss more about how I can help company X” will work
Formal Salutations
End the cover letter in a professional manner. Something like “Kind regards” or “Sincerely” will be proficient.
For more inspiration, read our step-by-step guide on how to write a cover letter.
Key Takeaways
Congrats!
If you followed all of the above advice, you’ve given yourself the best possible chance of landing that data scientist role.
Let’s quickly summarize what we’ve learnt:
- Format your data scientist resume correctly by prioritizing the reverse-chronological format and then following the content layout guidelines
- Start your resume with a summary or objective to hook the recruiter
- In your work experience section, give attention to your best achievements, rather than your responsibilities
- Craft a convincing cover letter for an unbeatable application
