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7 Entry-Level Data Analyst Resume Templates with Example

By Ria · Last Updated On October 22, 2026
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This guide shows you how to build an Entry-Level Data Analyst resume that makes your analysis skills and evidence easy to review. You will learn how to organize relevant projects, education, tools, and results for a clear first read.

Strong resumes for this role connect methods to outcomes. Use concise bullets to show how you cleaned and checked data, analyzed patterns, and explained findings, with tools such as Java, SQL, Python, Excel, Tableau, and Power BI where accurate.

Compare the same resume presented in 7 layouts through image previews, then open an example in the editor to review or customize its structure.

What Makes a Great Entry-Level Data Analyst Resume in 2026

A strong Entry-Level Data Analyst resume uses clear sections, focused skills, and concise bullets that show how analysis work was completed and shared.

Include accurate keywords such as Java, SQL, Python, Excel, Tableau, data validation, and data visualization. Support them with project details, methods, and results that readers can verify.

Note: Resume examples are for educational purposes only. Use only information that accurately reflects your experience and qualifications. References to real organizations do not imply affiliation or endorsement.

#1 Simple One Column Format Resume Example

A single-column reading path keeps resume sections in sequence, giving reviewers a straightforward way to follow the document.

 
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Why This Format Works

  • One reading path keeps education, projects, and experience in a clear sequence.
  • Project bullets stay together, helping reviewers follow methods and reported findings.
  • A simple section order makes skills and credentials easy to locate.

Best For

  • Linear section review
  • Project-focused experience
  • Education and experience in sequence
  • Skills and credentials review
  • Text-led resume presentation

Resume Keywords

  • Bachelor of Science in Computer Science
  • Apply Java programming
  • independent learning
 

#2 Simple Two Column Format Resume Example

Two columns place resume content side by side, a practical choice when reviewers need to scan distinct sections across the page.

 
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Why This Format Works

  • Two content areas separate experience from supporting sections for easier review.
  • The side-by-side structure helps reviewers move between education and experience.
  • Distinct areas give skills and achievements clear places in the resume.

Best For

  • Side-by-side section review
  • Project and academic history
  • Skills with supporting details
  • Education beside experience
  • Quick resume section navigation

#3 Plain One Column with Shaded Labels Resume Example

The one-column structure gives this resume a direct reading order, which suits a review that follows education, projects, and experience from top to bottom.

 
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Why This Format Works

  • A top-to-bottom order helps reviewers trace project and academic experience clearly.
  • The single reading path keeps achievement details connected to their entries.
  • Skills and education remain easy to find within the document sequence.

Best For

  • Top-to-bottom resume review
  • Academic project history
  • Chronological experience reading
  • Skills and education sections
  • Straightforward document structure
 

#4 One Column Format with Photo Right Resume Example

A photo set on the right accompanies the one-column resume, offering a clear photo presentation while keeping the document content in one reading path.

 
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Why This Format Works

  • The single column keeps experience and education in a direct reading sequence.
  • Project details remain together, making methods and findings easier to follow.
  • A separate photo area leaves resume sections in a continuous content path.

Best For

  • Right-side photo presentation
  • Single-path resume review
  • Project-centered academic history
  • Continuous experience reading
  • Photo-inclusive document layouts
 

#5 Clean Two Column Sidebar Format Resume Example

The two-column structure creates a side-by-side view of resume sections, helping reviewers locate information without following one long vertical sequence.

 
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Why This Format Works

  • Separate content areas help reviewers distinguish experience from supporting resume sections.
  • Two-column reading gives education and skills clear, nearby points of reference.
  • Project achievements can be reviewed without losing sight of other sections.

Best For

  • Side-by-side content review
  • Project and research experience
  • Education with skills
  • Resume sections read in parallel
  • Compact information organization
 
 

#6 Two Column Format Resume Example

Two columns give the resume a parallel reading structure, useful when reviewers want to compare work history with other document sections at a glance.

 
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Why This Format Works

  • Parallel content areas make experience and education easier to review together.
  • The two-column reading structure supports quick movement between resume sections.
  • Skills and project achievements remain distinct parts of the document.

Best For

  • Parallel section comparison
  • Academic project details
  • Experience and education review
  • Distinct skills sections
  • Fast document navigation
 

#7 Photo Header Two Column Format Resume Example

A photo paired with a two-column resume body combines photo presentation with side-by-side content, a useful option for readers who prefer both features.

 
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Why This Format Works

  • Two columns let reviewers scan experience alongside other resume sections.
  • The paired content areas make education and skills easier to locate.
  • Project details remain within a structure that supports side-by-side review.

Best For

  • Photo with two-column content
  • Side-by-side resume sections
  • Academic project experience
  • Skills and education overview
  • Parallel information review
 
 
 

See Also

 

Frequently Asked Questions

Are these Entry-Level Data Analyst resume templates ATS-friendly?

The examples use readable sections and clear headings. Use standard section names and include relevant terms such as Java, SQL, Python, data cleaning, and data validation when they match your experience.

What should an Entry-Level Data Analyst resume include?

Include a focused summary, education, relevant projects or experience, technical skills, and certifications. Use bullet points to explain the data, methods, tools, and results for each project.

How can I show data analysis experience from academic projects?

Name the project and dataset, then describe the steps you took, the tools you used, and what you presented. Include details such as data checks, documented methods, or findings when they are accurate.

Which resume layout works well for an Entry-Level Data Analyst?

Choose a clear layout with familiar headings and a logical section order. A simple one-column structure can make skills, education, and project bullets easier for people and ATS software to scan.

Should I list tools such as Tableau and Power BI?

List tools you have used and can discuss. Connect each tool to a project or task, such as building a chart, preparing a report, or checking data.

Can I compare the resume examples before editing one?

Yes. Review the PNG image previews to compare the layouts, then open an example in the editor to view or customize it.

ATS score and resume checks

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ATS Score 76%

How we calculate this score

  • Keywords: 60% of the total. AI extracts keywords from your job description. If you do not provide one, a standard job description for the title matching your resume is used. This is not a match to a specific vacancy.
  • Text-based resume: 20%. The text resume assessed here receives 100 for this part.
  • Resume quality: 20%. We start at 100 and subtract points for issues found by our resume checks, down to a minimum of zero.
  • Keyword coverage = round(100 × confirmed matches ÷ total keywords). Exact matches and supported equivalents verified by AI receive full credit; unsupported keywords receive none. Live text checks use the saved equivalents and do not request a new AI review. Without keywords, no overall ATS score is available.
  • Final score = 60% of keyword coverage + 20% of the text score + 20% of the quality score, rounded to a whole number. Without keywords, no overall ATS score is available.

What this score means

Our scores are estimates, not employer ratings. They may contain errors and do not guarantee accurate parsing, a ranking, an interview, or a job. Check your document against the employer’s requirements. You are responsible for relying on this score.

Terms and Conditions

Score weights: Keywords 60% · Text based resume 20% · Resume quality 20%

Keyword coverage: 3 of 5 (60%) · Resume quality: 100%

Resume quality 100% · Weight 20% · Issues (0)

Details
  • ✓Name present: Brayden Manning
  • ✓Email format: brayden.manning@example.com
  • ✓Phone format: (513) 555-XXXX
  • ✓Experience 1: Job title: Data Analyst Capstone Project
  • ✓Experience 1: Company name: University Capstone Project
  • ✓Experience 1: Work location: Cincinnati, OH
  • ✓Experience 1: Employment dates: Aug 2024 - May 2025
  • ✓Experience 1: Description or achievements: Present
  • ✓Experience 2: Job title: Student Data Analysis Research Project
  • ✓Experience 2: Company name: Academic Research
  • ✓Experience 2: Work location: Cincinnati, OH
  • ✓Experience 2: Employment dates: Jan 2024 - May 2024
  • ✓Experience 2: Description or achievements: Present
  • ✓Experience 3: Job title: Data Analysis Programming Lab
  • ✓Experience 3: Company name: Student Lab
  • ✓Experience 3: Work location: Cincinnati, OH
  • ✓Experience 3: Employment dates: Sep 2023 - Dec 2023
  • ✓Experience 3: Description or achievements: Present
  • ✓No placeholder fields
  • ✓No repeated achievement bullets
  • ✓No empty bullets

No issues found by the current checks.

Text Based Resume 100% · Weight 20%

Parsed text
Brayden Manning
(513) 555-XXXX
brayden.manning@example.com
braydenmanning
Cincinnati, OH 45202
SUMMARY
Early-career Data Analyst with a Bachelor of Science in Computer Science and academic experience analyzing public transit and campus energy datasets. Apply Java programming, SQL, Python, Excel, Tableau, and Power BI to prepare information, verify calculations, and present clear findings. Document data decisions and limitations so classmates and faculty can review the methods and interpret results accurately. Pursue technical growth through independent learning, feedback, and hands-on practice, with particular interest in turning open-ended questions into organized, testable analysis.
EDUCATION
Bachelor of Science in Computer Science
2025
University of Cincinnati
Cincinnati, OH
TECHNICAL SKILLS
Programming Languages: Java, Python, SQL
Spreadsheets: Microsoft Excel, Google Sheets, LibreOffice Calc
Data Visualization: Tableau, Microsoft Power BI, Looker Studio
Relational Databases: MySQL, PostgreSQL, SQLite
Java Development: JUnit, Maven, Gradle
Python Data Libraries: pandas, NumPy, Matplotlib
Notebook Platforms: Jupyter Notebook, Google Colab, Apache Zeppelin
Version Control: Git, GitHub, GitLab
Data File Formats: CSV, JSON, XML
Database Connectivity: JDBC, ODBC, SQLAlchemy
SKILLS
Data analysis
Data cleaning
Exploratory analysis
Data validation
Statistical analysis
Java programming
SQL querying
Python analysis
Excel analysis
Tableau visualization
Power BI reporting
Data visualization
Research documentation
Technical presentation
Independent learning
EXPERIENCE
Data Analyst Capstone Project
Aug 2024 - May 2025
University Capstone Project
Cincinnati, OH
Examined approximately 180,000 public transit trip records using Python, SQL, and Excel to investigate service reliability, documenting cleaning rules and exclusions so the analysis could be reproduced.
Built Tableau views comparing route-level delays and time-of-day patterns, then presented findings and data limitations to faculty and classmates in a final project review.
Cross-checked summary calculations between SQL queries and spreadsheet outputs, resolving inconsistent date and route fields before publishing the project dataset and report.
Student Data Analysis Research Project
Jan 2024 - May 2024
Academic Research
Cincinnati, OH
Analyzed campus energy-use records with Excel and Python for a supervised study, organizing monthly readings and flagging missing observations before comparing seasonal patterns.
Prepared charts and concise research notes that connected observed trends to the study questions while distinguishing measured results from possible explanations.
Presented the methods and findings to a faculty review group and incorporated feedback on labeling, source documentation, and interpretation.
Data Analysis Programming Lab
Sep 2023 - Dec 2023
Student Lab
Cincinnati, OH
Used Java programming to read and validate sample transaction files, applying conditional checks to identify malformed rows and producing consistent summary counts for course exercises.
Compared program output with hand-checked samples, documented test cases and edge conditions, and presented the processing approach as part of a data structures lab.
LEADERSHIP, AWARDS & RECOGNITION
Received student presentation recognition at the Computer Science Department Project Showcase in 2025.
Named to the University of Cincinnati Dean's List for Fall 2023 and Spring 2024.
Facilitated weekly introductory programming study sessions during the 2024 academic year, helping peers practice course concepts.
Coordinated a beginner-friendly spreadsheet and data visualization workshop with the campus data science student group in 2024.
CERTIFICATIONS
Google Data Analytics Professional Certificate
2025
Java Programming and Software Engineering Fundamentals Specialization, Coursera
2024
PROFESSIONAL AFFILIATIONS
Student member, Association for Computing Machinery (ACM), engaging with a professional community focused on computing and data practice.
Student member, IEEE Computer Society, participating in an organized community for computing professionals and students.

Matched keywords (3)

  • Bachelor of Science in Computer ScienceOriginal keyword in JD: Bachelor's OR Master's degree in Computer Science OR Computer Engineering OR Electrical Engineering OR Information Systems OR Information Technology
  • Apply Java programmingOriginal keyword in JD: Java programming experience
  • independent learning

Missing keywords (2)

  • Motivation
  • Technical curiosity
Disclaimer: All names, images, contact information, employment histories, achievements, security clearances, military credentials, and other qualifications shown in this content are fictional and used for illustrative purposes only. Any resemblance to actual persons, living or deceased, is purely coincidental.

Resume and cover-letter examples and recommendations in this article reflect general best practices and professional experience and are provided for guidance only. Results may vary based on role, industry, region, and hiring organization.

Content Accuracy and Verification: To the fullest extent permitted by applicable law, we do not represent or warrant that resume or cover-letter guidance, examples, recommendations, or related information are accurate, complete, current, error-free, or suitable for any particular purpose. You are responsible for independently reviewing and verifying the information before relying on it.

ATS and Cover-Letter Scores: ATS scores are estimates calculated using our own formula, informed by publicly available guidance on resume formatting and keyword matching. They are not scores issued or endorsed by an ATS provider or employer. Cover-letter scores are also our own assessments. Parsing, weighting, screening criteria, and results vary between systems, employers, job descriptions, and document formats. No score guarantees successful parsing, a particular ranking, an interview, or employment. Use scores as general guidance and independently check your documents against the employer’s requirements. To the fullest extent permitted by applicable law, we accept no liability for errors in scores or parsing, or losses arising from reliance on these assessments. Nothing in this notice excludes liability or limits consumer rights that cannot lawfully be excluded or limited.

Terms and Conditions
 
 
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