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With advancement in technology over the years, it has become almost impossible to escape data. As per the US Bureau of Labor Statistics reports, data scientists are projected to grow by 31%.

To bag a decent job in the current market, you need to create a recruiter-friendly resume following updated industry standards. Lucky for you, this guide will provide you a well-rounded source for all those tips

Here are the entry level data scientist resume tips to create the best entry level data scientist resume:

Data Scientist Salary

The salary of a data scientist depends on various factors including place of work, seniority level, location, and so on. However, you can get higher pay by developing your skills and being updated with industry trends.

Here is a list of data scientist salaries based on cities:

City Data Science Salary
San Francisco $121,836
Seattle $108,399
New York $101,387
Boston $101,064
Los Angeles $99,014
Austin $96,495
Atlanta $91,049
Washington, D.C. $89,738
Chicago $88,758
Charlotte $87,306

Entry Level Data Science Resume Formats

Your junior data science resume may get rejected despite being up to date. It could be because it did not get past the ATS, which most companies have as of late. Along with including all of your professional details, you must ensure that your data science resume is ATS-friendly.

To hold together your details together, you need to pick the most suitable resume format.


Also read: How do I make sure my resume is ATS-compliant?

Chronological Format:

This format has a time based approach, highlighting most recent experience first. It gives a clear insight into your career trajectory.

Along with being recruiter-friendly, it is also ATS-friendly because of it's error-free structure. It also shows that the candidate has nothing to hide, so if you have gaps in your resume, you might want to skip this one.

Functional Format

It is used by professionals who changed their industries and by those who have gaps in their professional experience timeline. However, it has the con of being non-ATS-compliant.

Combination Format:

You can opt for resume format if you have vast experience in your field of work. This format allows you to broadly highlight your skills as well as describe your work experience

Also read: How and when to use the correct resume format?

Organize Your Entry Level Data Science Resume

An ideal resume should contain all the distinct sections that can make the resume ATS-compliant as well as recruiters-friendly.

The following is a list of the traditional resume sections:

  • Header
  • Personal Information
  • Profile Title
  • Summary/Objective
  • Key Skills
  • Professional Experience
  • Education

You can provide the details of the following to further explore your professional and academic achievements:

  • Certifications (if any)
  • Awards & Recognition (if any)
  • Additional Information (if any)

Also read: How to divide a resume into different sections?

Optimize Your Data Science Resume Header

The topmost section of your data science resume is an ideal segment to label your resume and provide your personal information.

Entry Level Data Scientist Resume: Header

Your junior data science resume needs to be labeled with your name to distinguish yourself from the other applicants.

Follow the given tips to frame a flawless resume header:

  • Write your resume header in the largest font size of 16-20 points.
  • Leave a single space between your first name and last name.
  • If you have a middle name, write only the initial of your middle name followed by a period.

Entry level data scientist resume sample for header:


Hiration pro tip:
Do not waste your time and precious space in your data science projects for resume by writing "Resume" or "CV" because there is no point.

Entry Level Data Scientist Resume: Personal Information

You should provide the following details in an ideal personal information section of your data science resume:

  • Updated Contact Number
  • Professional Email Address
  • Current Location
  • GitHub/Kaggle link
Hiration pro tip:
You can also provide the link to your social profiles like LinkedIn so that the recruiters can get in touch with you.

Updated Contact Number

While giving out the contact number you need to make sure that it is correct and active so that the recruiters can easily reach you.

Some recruiters may want to interview you over the phone or simply call you up to get a confirmation for any face to face meetings.

Tips to write the contact number on data science entry level resume:

  • Always mention your personal number, not your parent's or someone else's.
  • Write the country ISD code in front of your contact number and use a plus(+) sign before the ISD code

Professional Email Address

Avoid giving out any email address that has a made-up name because it is not considered professional. Your email address should always have your real name.

Practice this:
  • johndoe27@gmail[dot]com
  • john.doe@gmail[dot]com
  • doe.john03@gmail[dot]com
Avoid this:
  • iamj0hn3283@gmail[dot]com

Current Location

If you are considering a job in some other country other than yours then you can mention your location as city, country code

Else simply mention your location as city, state code.

There is no need for you to mention your personal home address in your entry level data science resume template so make sure that you avoid unnecessary details like your house number, street name, etc.

As an entry level data scientist, the candidate must have experience in conducting academic projects. Such projects give a glimpse of the candidate's skills to the hiring manager through GitHub or Kaggle.

Aside from that, you can also include your LinkedIn profile, if it is updated and active. It will help recruiters explore your candidacy and make sure if you are the right fit for the job.

A lot of recruiters prefer candidates who give their LinkedIn profile because it allows a lot of room to review their application, more than other applicants.


Data science resume sample for contact information section:


Also read: How to compose a crisp contact information section?

Entry Level Data Scientist Resume: Profile Title

Your profile title is the representation of your professional status in a resume and needs to be accurate at all times.

The profile title in your data science resume can communicate the following facts to the recruiters:

  • Your current designation.
  • Your functional industry.
  • Your level of professional seniority.

Here is what you need to do while framing your profile title in a resume for data scientist:

  • It should be the second-largest text in the resume after your resume header.
  • It should ideally be framed in the 14-16 font size.

Here is a snapshot of an ideal profile title from our entry level data scientist resume template:


Perfect Your Entry Level Data Scientist Resume Professional Experience

The professional experience section is one of the most important sections of your data science resume. Since a lot of companies use the ATS, you must make sure that your resume writing standards are updated and recruiter-friendly.

Here are some tips you can follow:


Framing Points:

  • You need to break down your work record in one-liner entry level data scientist resume points
  • Start your points with a power verb to discuss your work history
  • Validate your achievements by mentioning achievement figures

Grouping & Highlighting:

  • Create different headings and list all the similar points under relevant subheadings
  • Select words or phrases that throws light into your productivity and bold them

Doing so can make the recruiters acknowledge your professional involvement in executing the roles and responsibilities assigned to you.

Also read: How to craft a job-winning professional experience section?

Look at the ideal entry level data scientist resume example of the professional experience section presented through our data science resume sample given below:


Include Your Educational Details in Your Entry Level Data Scientist Resume

A data science resume is incomplete without the education section.

To be a Data Scientist you need to have a Bachelor's degree in Computer science, Social sciences, Physical sciences, and any relevant field of study. If you have more than a Bachelor's degree make sure to mention the same.

Here is a list of the details that you need to provide:

  • The name of the school/university
  • The location of your school/university.
  • Joining and graduation dates in the mm/yy format
  • Relevant course modules

There is an advantage of providing your educational details, especially if you are writing an entry level data scientist resume. Your lack of experience can be covered with the educational qualification that you hold.

To further help you get a clear picture of an ideal education section of a resume, here is a snapshot of our entry level data scientist resume sample:


Entry Level Data Scientist Resume Certifications

Get the attention of the recruiters by providing the details of your certification(s).

If you are a certified data scientist, it can have a positive impact on your job application and make the recruiters give you extra credit.

The certifications section of your data science resume can help you communicate the following details about you to the recruiters:

  • Certification course name.
  • Name of the institute of affiliation.
  • Completion date of the course in the mm/yy format.

Here are a couple of entry level data science certifications:

  • Cloudera Certified Associate (CCA) Data Analyst
  • Cloudera Certified Professional (CCP) Data Engineer
  • Data Science Council of America (DASCA) Principle Data Scientist (PDS)
  • Dell EMC Data Science Track (EMCDS)
  • IBM Data Science Professional Certificate
  • Microsoft Certified: Azure Data Scientist Associate
  • Open Certified Data Scientist (Open CDS)
  • SAS Certified Data Scientist

Here is an entry level data science resume example showcasing the ideal certifications section for your data scientist entry level resume:


Entry Level Data Science Resume: Additional Information

There are various details that you can mention in your junior data scientist resume.

For example, if you have the ability to speak or write more than one language you should mention the same in your junior data scientist resume.

Doing so can make you stand out as an applicant who has the ability to communicate with others who speaks a different language.

Apart from these, you can always provide the details of any extracurricular activities that you have been involved in to emphasize your experience in creative learning, especially as an entry-level applicant.

Such extra details will help you in communicating your soft skills effectively and be considered as an active student and professional. However, it would be a waste of space if you are an experienced professional, because at that point recruiters care more about hard skills.

Entry Level Data Science Projects for Resume

Including your academic projects in your data science resume is a good way to attract recruiters' attention. It helps the recruiters gauge your skills and work experience which will help you stand out from the crowd.

Here are the steps to write a perfect data science projects for resume section:

  • Give a short project description
  • Mention the tech stack of the project
  • List your roles and responsibilities along with some of the accomplishments of the projects with figures

Project: Readme Analysis | Tech Stack: Tableau, Scikit-learn, SQL

  • Deployed NLP to understand the programming language used in the repo with 89% accuracy
  • Employed an API to transcode the programming language into a read me file for each report

Present Your Entry Level Data Scientist Resume Skills

The skills section is another important segment of your data science skills resume wherein you can inject suitable keywords that can help your data science resume get past the ATS.

Go through the professional experience section of your best entry level data scientist resume and pick the skills that elucidate your professional caliber.

Avoid cramping up the skills section with phrases as it may affect the effectiveness of your data science skills resume.

The whole point is to make the skills section crisp and make the recruiters recognize your potential as a data scientist.

Another thing you need to do while farming your skills in your junior data science resume is to create separate sections to highlight your technical and functional skills.

Here are some of the data science resume key skills:

Key Skills
Data Analysis Data Mining
Predictive Modeling & Analytics Machine Learning
Data Visualization Sentiment Analysis
Text Mining Software Debugging
Programming Project Management

Technical Skills:

Technical Skills
Python R
SQL Java
JavasSript Matlab
Tableau Scikit-learn
Tensor Flow Spark

Here is a data science resume example to help you see what an ideal skills section should look like in a data science resume:


Curate an Impeccable Overview of Your Entry Level Data Scientist Resume

What goes in the first half of your resume depends a lot on your level of experience. You can either frame a resume summary if you have enough years of experience, or draft a resume objective if you are an entry-level professional.

Entry Level Data Scientist Resume Summary

A suitable resume summary for entry level data scientist should include some of the distinct professional experience that you have acquired over the years and also highlight your core skills.

Here is a list of all that you should do to compose your resume summary for entry level data scientist:

  • Write your summary at the end of resume-writing process as you will have a well-rounded mental overview of your work history.
  • Pick the highlights of your career from the work experience section of your resume.
  • Unless you have 10+ years of extensive work experience try not to exceed your resume summary to more than 3-4 lines.
  • Start your sentences with power verbs and make sure that you maintain a cause-effect methodology.

Refer to the data scientist resume example for an ideal entry level data scientist resume summary:


Entry Level Data Science Resume Objective

Give an overview of your data science entry level resume by composing a resume objective. You should include an entry level data science resume objective if:

  • You do not have any work experience.
  • You have less or limited work experience below 3 years.
  • You are a fresh graduate writing an entry level data scientist resume.

Instead of asking what the organization can provide you, rather examine what you can contribute to the organization, which is what you should include in an objective.

The ideal resume objective should be able to communicate your willingness to learn from the roles and responsibilities that would be given to you, along with highlighting your skills as a professional data scientist.

Entry Level Data Scientist Sample Resume

Before we go ahead with more about resume-writing, here is our complete data science resume template to help you understand what an ideal resume should look like:

Edmund Best
Associate Data Scientist
5+ years experienced data science professional and Cloudera certified associate adept at enhancing advanced analytics and conducting operational research to support the go-to-marketing strategies. Possesses diverse experience in executing projects, validating techniques, and gathering requirements as part of ensuring business growth & development. Proficient in cleaning and transforming data to provide data-driven recommendations and conducting statistical analysis to identify performance patterns.
• Data Cleansing & Transformation • Statistical & Data Analysis • Feature Design & Implementation • Solution Delivery
• Machine Learning • Mathematical Programming • Econometrics • Simulation • Requirement Gathering & Translation
• Analytics Enhancement • Operational Research • Project Execution • Technique Validation • Business Development
  • Software & Website: SAS, Google Cloud Analytics
  • Programming Language: Python, R, C, C++
Feline Corporation Ltd.
Start typing, then use the up and down arrows to select an option from the list
    A multinational professional services company with revenue worth USD 43 billion
    Data Analytics Enhancement
    • Enhancing the advanced data analytics for supporting all go-to-market-strategies as part of a 60 member data science team
    • Leveraging expertise in data-driven science in B2B commerce to increase intelligence in the go-to-market functionality
    Operational Research
    • Employing mathematics, statistics, econometrics, and operations research for developing machine learning solutions
    • Contributing to diverse fundamental science research programs for studying human health problems like cancer & infections
    Project Execution
    • Executing independent data science projects with 20 customers for solving specific business problems
    • Administering data science projects for configuring the solutions to maximize value for the customers
    Technique Validation
    • Exploring and validating new techniques to incorporate into price segmentation
    • Participating in the development, validation, and delivery of reporting tools
    Business Development
    • Converting opportunities into product modules that are valuable across multiple industries
    • Conducting technical research while leading and mentoring a team of 10 senior data analysts for business development
    Ansoft Pvt. Ltd.
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      The world’s largest pure-play Big Data Analytics and Decision Sciences company with a Unicorn status in the US and an employee base of 5k professionals
      Requirement Gathering & Translation
      • Rendered assistance in translating requirements into technical specifications for data and reporting teams
      • Translated requirements into design solutions for 20 business leaders, stakeholders, product managers, and internal teams
      Data Cleansing & Transformation
      • Leveraged quantitative skills extensively to clean, transform & interpret raw data for providing data-driven recommendations
      • Extracted, processed, and analyzed large data to solve the most pressing analytical issues
      Statistical & Data Analysis
      • Performed statistical analysis to identify internal performance pattern & devised data-driven strategies to optimize the same
      • Improved business by 60% by conducting data analysis and executing projects for driving business recommendations
      Feature Design & Implementation
      • Designed, implemented, analyzed, and tested 4 new features to improve the product suite
      • Developed 7 end-to-end business intelligence solutions to advance Power BI functionality and features like Power BI server
      Dashboard Development
      • Crafted and delivered 6 performance monitoring dashboards to track business performance
      • Conceived, built, launched, and maintained 4 dashboards to improve AV operations
      Brisco Ltd.
      Start typing, then use the up and down arrows to select an option from the list
        An American professional services firm headquartered in New York City, NY and revenue worth USD 3 billion
        Solution Delivery
        • Liaised with 10 colleagues from sales, operations, product and finance teams to deliver solutions for improving operations
        • Built 2 reporting and metrics tracking solutions to optimize cash management
        Framework Development
        • Conceptualized frameworks and quantitative models to seize new business ventures
        • Developed 6 dashboards and frameworks to monitor business performance while creating business cases
        • Drafted monthly reports on sales performance including operations & profitability to identify opportunities for improvement
        • Developed 60 reports on client usage and performance prior to contract renewals to suggest best products for client scenarios
        Business Development
        • Formulated and managed 10 execution plans of business intent to monitor results
        • Built strategies and improved the profitability of the network by 10% while solving complex business problems
        Data Translation
        • Interpreted learnings into data pull and visualization for automation while creating metadata specifications for compliance
        • Construed business requirements into proposed data definitions for creating 10 policies as per industry standards
        • Certified Analytics Professional | Marble Academy | Berkeley, CA | Jul '20 - Dec '20
        • Cloudera Certified Associate: Data Analyst | Cloudera | Jan '18
        Eastview University
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          A public research university in Sparkill, NY with a student base of 45k+ students
          • 3.8/4.0
          • Languages: English (Native) and Vietnamese (Interactive)

          Key Takeaways

          Here are some key takeaways from the guide to help you write a job-winning data science resume:

          • Always make it a point to draft your data science internship resume in a suitable resume format.
          • Label your resume with your name and provide your personal information in line with the hiring guidelines.
          • One-liner points have a higher chance than paragraphs to be read by the recruiters and comprehend your work experience statements.
          • Provide achievement figures to give the recruiters an idea of what you are capable of contributing to an organization's higher goals.
          • Give an overview of your resume by including a suitable data science resume summary.
          • Include data science projects to enhance your candidacy and show your expertise.

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