Data Scientist Resume Guide & Tips

Creating a professional resume is an essential part of securing a job as a Data Scientist. Resumes often serve as the first touchpoint between you and a recruiter. A strong resume will highlight your experiences, strengths, and reflect how you match the qualifications needed for the position. The following sections offer tips and best practices for creating a Data Scientist resume.

What to Put on a Data Scientist Resume

There are a few key elements every professional resume should include. Your resume should always list your skills, education, and contact information. When applying for a Data Scientist position, there are additional items your resume should include. Data Scientist resumes should highlight your data science knowledge, skills, and experience by including the following. 

Name and Contact Information 

The first thing to include on your resume is your name and contact information. After all, a recruiter can’t follow up with you about the position if they don’t know who you are or how to get in contact. Your name and contact information should appear in the resume header at the top of the page. Depending on the resume format you choose, your name may appear in the upper left corner with your contact information in the upper right. You could also display your name in the upper left corner and include your contact information on the lines below it. You should also include either your current job title if relevant to the position or the job title you are aspiring for such as “Entry-level Data Scientist.” 

Contact information should include:

• Your phone number 
• Email address
• URL of your LinkedIn profile (with full URL displayed in case resume is printed)
• A link to your professional data science portfolio

Career Objective or Summary

The career objective and summary section indicates your professional goals in relation to the position you are applying for. This statement should also highlight how your characteristics and work style make you an excellent candidate for this position. Here are some tips to keep in mind while crafting your career objective/summary: 

• Use complete sentences rather than a bulleted list for this section. Summarize your experience, your knowledge, and your goals for the next step in your career.
• Highlight any experience directly relevant to this position. If you are starting a new career, you can summarize your professional career so far and state why you are looking to begin a career as a Data Scientist.
• Mention the industry you have worked in and your previous roles as a summary of your professional background.
• Tailor this statement to the job you are applying for. Data Scientists work for organizations in various industries and fields. For example, your statement when applying to a Data Scientist position at a government agency may look quite different from a statement you submit for a technology company.

Here is an example of career objective/summary for an entry-level Data Scientist position: 

• I am an entry-level Data Scientist with a passion for science and innovation. I use my analytical mind, team-oriented attitude, and problem-solving experience to help organizations achieve their objectives.

Education, Awards, and Certifications

The education section of your resume should include the following:

• Postsecondary degrees earned starting with the highest. Also include the year you earned it and the name of the school
• Any awards your work has received 
• A list of professional certificates relating to data science
• A list of any professional certifications earned, especially those pertaining to data science

The exact way of formatting this section depends on the resume format you choose, but a common way of structuring this section is: 

Level of Degree (B.S., B.A., PhD, etc.)

Degree Topic (Computer Science, Statistics, etc.)

School Name

Graduation Date

School location 

GPA (Optional)

You can also use this section to highlight any data science education you have, such as a data science certificate.

Quantitative Impact

As a Data Scientist, you will help measure the success of an organization’s efforts and help determine future goals by calculating and sharing key performance metrics. Your resume should include metrics such as how your past efforts have led to measurable improvements. For example, by analyzing the average customer wait time and working alongside leadership in Customer Support, you could automate certain tasks, thus increasing efficiency and reducing the wait time by five minutes. Highlight this achievement making a statement such as: 

• Created and implemented use of chatbot, reducing customer wait time by 50%

Quantifying your achievements makes it clear exactly how valuable you have been to past organizations and how valuable you will be as an addition to the team. 

Data Science Portfolio

You’ve heard the expression that the proof is in the pudding. When it comes to resumes, the proof is in the portfolio. A data science portfolio provides evidence of your knowledge and skills. It also confirms the professional experience that you outline in your resume. Just as you should tailor your resume to each position you apply for, you should choose the portfolio projects that highlight skills and experience most relevant to this specific job.

If you have worked in a data science role previously, you may have samples of real-world projects that you can include. If you are new to data science or aspiring to become an entry-level Data Scientist, you can include projects you have worked on as part of your data science training. Data science courses and programs that include hands-on activities help you simultaneously learn and retain information, develop your skills, and contribute to your data science portfolio. Whenever possible, have a mentor or trusted professional review your portfolio. Their feedback can help you make the best possible impression through the work you showcase. Reviewing a portfolio with a mentor can also ensure your projects truly highlight your abilities. Rather than submitting a cookie-cutter portfolio, create one that stands out from other applicants. 

A data science portfolio might include:

• An example of your programming knowledge 
• An example of documentation you’ve created
• Writing samples, data visualizations, and reports that show that you can effectively communicate your findings to stakeholders

These projects fall into two camps: code-based projects and content-based projects. A strong portfolio will contain a blend of both. 

Learn more about creating a data science portfolio.

Programming Languages, Data Science Tools, and Other Skills

Use the skills section of your resume to highlight skills directly relevant to the job you are applying for. For a Data Scientist role, this will likely include:

• Programming languages 
• Data science tools
• Artificial intelligence (AI) and machine learning (ML) skills
• Skills in supervised and unsupervised learning
• Soft skills such as communication and teamwork
• Any skills the prospective employer highlights in the job description

5 Data Scientist Resume Tips

Now that you know what your resume should include, you’re ready to structure and review it to ensure that it conveys your professionalism. Did you know that recruiters spend just seven seconds on average looking over an individual resume? This means that your resume needs to make a positive, powerful impression. The following tips will help you create a clean, engaging resume that stands out from other applicants while communicating your skills, knowledge, and experience.

There are different ways you can choose to structure your resume. The three main types of resume structures are:

• Reverse-chronological
• Functional
• Combination

The structure you choose will largely depend on which elements of the resume you wish to highlight above others. If you aren’t sure which structure will best showcase your skills and experience, consult with a mentor or another professional who can review your resume. 

Using the Reverse-chronological Resume Structure

The most common resume format, especially among experienced professionals, is the reverse-chronological structure. This structure is the kind that recruiters see most often, which makes it a good choice for simply and efficiently communicating your qualifications. This structure emphasizes your professional experience and skills, which is particularly helpful if you are looking to advance in your current field or your professional experience directly relates to the job you are applying for. This structure displays your professional roles starting with your most recent job title and progressing in reverse-chronological order. The education section of a reverse-chronological resume should also follow this structure. So your most recent degree or certificate would display on the first few lines of this section, followed by other degrees or certificates.

The one drawback to the traditional reverse-chronological resume is if you lack experience in the field you are looking to start a career in. For this reason, recent graduates or those who are changing careers may wish to consider using a functional or combination resume structure. 

Using the Functional Resume Structure

The functional resume structure, also called a skill-based resume, emphasizes your skills rather than work experience. This type of resume is typically structured as follows: 

• Contact information
• Career objective/summary
• Skills and strengths
• Additional sections
• Education

Because this resume structure focuses on skills, you should elaborate and make this section longer than you might in the reverse-chronological format. The intention of highlighting the skills section is to communicate to the computer that you possess the skills needed for the job. Your skill section should include your data science and other hard skills, but also soft skills such as teamwork, communication, and leadership. 

One drawback to this format is that, being that it is uncommon compared to the traditional reverse-chronological resume, it could throw recruiters off or they may suspect you are seeking to hide your lack of experience. 

Using the Combination Resume Structure

You can also opt to use a combination resume structure, also called a hybrid structure. To have a balanced focus on work experience and skills, consider the following structure: 

• Contact Information
• Career objective/summary
• Skills and strengths
• Additional sections
• Education

Choosing How to Format Your Resume

Whichever resume structure you choose, there are some key formatting tips to follow: 

• Keep your resume to a single page
• Use a clean, easily-readable font such as Roboto or Ubuntu
• Save your resume as a PDF or Word document
• Prioritize highlighting your achievements over your responsibilities 

Get Feedback

Whenever possible, have a trusted professional or mentor review your resume. A Data Science Certificate program that includes one-on-one mentoring provides the opportunity to have your mentor or teacher review your resume. Using their feedback, you can tailor your resume to the position you are applying for and polish your resume so it stands out from other applications. Mentoring sessions can also be used to build and polish your portfolio, which is another key part of starting your career as a Data Scientist. Other benefits to look for in a data science course or program include a free retake, job search assistance, and setup assistance. Whether you choose to attend an in-person class or a live online course, having an instructor provides another professional who can review your resume.

Learn the Skills to Become a Data Scientist at Noble Desktop

If you are looking to start a new career in data science, you might think the only way for you to become a Data Scientist is by enrolling in a four-year university or pursuing other costly and lengthy educational options. However, there are many alternative methods available to help you transition into a data science career, including data science bootcamps and certificate courses designed to help working professionals gain the skills needed to obtain an entry-level job as a Data Scientist. Exploring in-person and live online data science bootcamps and certificate programs can help you find the class that meets your career goals, budget, and schedule. The first step to finding the class that fits your needs is to understand the differences between in-person classes and live online classes. 

In-person data science classes meet in a traditional classroom setting at a physical location. In-person classes have the advantage of providing all necessary equipment, such as computers and software, and allowing students to network with local professionals such as your classmates and instructor. You also have the advantage of learning from an expert instructor face-to-face. The primary drawback to in-person courses is the extra time and money required to commute to the physical learning location. Live online data science classes offer many of the same benefits as in-person classes, including the ability to learn in real-time from an expert instructor. You can also collaborate with classmates, and you have the advantage of learning remotely. 

Noble Desktop offers several different in-person and live online data science classes that can help you start a career as a Data Scientist. The Python for Data Science Bootcamp teaches students foundational programming concepts and how to handle different data types, use conditional statements to control the flow of a program, use Scikit-Learn, Matplotlib, Numpy, Pandas, and other Python libraries and tools. Noble’s Data Science Certificate program and Data Analytics Certificate program provide a deep dive into the topics and skills essential to launching a career in data science or data analytics and offer one-on-one mentorship and job search assistance. All Noble Desktop classes provide students with hands-on experience, flexible financing options, setup assistance, a free retake, small class sizes, and real-time guidance from an expert instructor.

Learn more about Noble Desktop’s in-person and live online data science classes.

You can also learn more about data science careers and data science learning options with Noble’s free Data Science Learning Hub.