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Data Scientist Resume Samples

Data science is a complex field of research that’s mostly based on trying to solve different problems with data. Oftentimes, it’s centered around helping with different business problems, but data science projects can range the gamut from governmental projects to NGO projects to private projects and beyond. If you want to make your resume shine, then here’s how to write a resume for any job posting.

What To Emphasize In A Data Scientist Resume

Your skills will always be the key component in a data scientist resume. Obviously, the more experience you get, the more you’ll rely on how you’ve used your skills to benefit different organizations. Therefore, the perfect resume for a data science position will always rely on the skills that you have, as this is a critical component of doing data science.

Tips for Writing a Data Science Resume

  • Don’t include your GPA on your resume. GPA typically isn’t required for a resume. Other honors like the cum laude will usually be more beneficial to feature.
  • Do tailor your resume specifically toward an application. This way, you’ll be able to showcase the right technical skills and experience to match the specific job position.
  • Do use the ResumeNerd resume builder to create your resume. While this builder is best if you don’t have a lot of experience with writing a resume, it can help you regardless of experience.

Data Scientist Resume Example

How To Build Your Data Science Resume

Any good data science resume needs to show off all the information that makes you a good data scientist. You want a recruiter to be able to read your resume and immediately know that you’ll be a great addition to the company. Here’s how.

1. Resume header

The resume header is part of the resume design overall. It usually includes your full name, contact information including your phone number, location, email address and links to job networking profiles such as your LinkedIn profile.

2. Resume summary and objective

Next is your resume summary and resume objective. These both feature two to three sentence paragraphs at the very top of a resume that generally summarizes your resume and talks about your best qualities. A resume objective is preferred when a job candidate lacks work experience. Instead, the objective discusses your career goals instead of years of experience.

3. Skills

In the data science field, your skills section could probably be lengthy. Recruiters will want to know about your skill set as a whole. Here are a few bullet points you can incorporate in the skills section of your resume:

  • Knowledge of machine learning
  • Finding and utilizing data sets
  • Programming languages (Python, SQL, Java, C#)
  • Writing and managing algorithms
  • Data visualization
  • Understanding big data
  • Data mining
  • General data analysis
  • Finding data sources
  • Using GitHub and Spark
  • General data modeling
  • Working with software utilities (Hadoop, Tableau)
  • Problem-solving
  • Creating data regression models
  • Deep learning
  • Building machine learning models
  • Predictive modeling
  • Understanding real-time data
  • Overall data analytics

On average, you’ll probably want to use five or six skills for a chronological resume and up to a dozen for a functional resume. Review your experience and select what skills you know you’re best at.

4. Work history

Your experience section is where you can include up to ten years of work experience, depending on the level of the position. A senior level applicant would possess more experience than an entry level job candidate. Many data scientist jobs can benefit from a data scientist resume sample. Here are a few:

  • Data analyst
  • Data modeling expert
  • Senior data scientist
  • Data engineer
  • Entry-level data scientist
  • Junior data scientist

All of these can be a great introduction to a professional resume. Additionally, be sure to provide measurable metrics in your job experience descriptions to showcase your skills throughout your resume.

5. Education

The last section of your resume is your education section. This is where you put your formal education and any certifications you have. Most of the time, data scientists have an education in computer science. Include your degrees here, as well as any other training and education you have.

FAQ: Data Scientist Resume Examples

Yes. A cover letter is important to include alongside any data scientist resume template. This is because the cover letter allows you to provide more interpersonal information than any resume format. It allows you to talk directly to the hiring manager, discuss elements of your work experience that you might not have been able to add to your resume and ask for a job interview directly. You can use a cover letter builder to make it easier for you to create yours.

If you’re writing an entry-level data science resume, then you might want to include relevant coursework on your resume as a way to make up for the fact that you likely won’t have a lot of work experience. However, as soon as you have more than around a year or two of work experience, you don’t need to include this coursework.

When you don’t have very many years of experience in data science, you might be struggling to look for a way to show a hiring manager that you have the skills necessary to do this type of job. In these situations, try to rely on your skills and education as much as possible, as well as any academic experience, volunteer work or internship experience you have.