7 Entry-Level Data Analyst / Data Scientist - Machine Learning Resume Templates with Example
This guide shows you how to build an Entry-Level Data Analyst / Data Scientist - Machine Learning resume that is clear, focused, and easy to review. You will learn how to organize relevant evidence and choose a format that supports your goals.
A strong resume connects analytical methods to clear results. Use concise bullet points to show how you prepared data, evaluated models, applied statistical reasoning, and shared findings.
The example is presented in 7 resume layouts so you can compare how different designs organize the same professional content. Review the image previews, then open an example in the editor to explore its structure.
What Makes a Great Entry-Level Data Analyst / Data Scientist - Machine Learning Resume in 2026
A strong resume uses clear section headings, focused skills, and concise bullets that show the purpose and result of analytical work. It should make projects, education, and relevant experience easy to find.
Use accurate role keywords such as Python, statistics, machine learning, large language models, Amazon SageMaker, Computer Vision, and data visualization. Support each skill with evidence from a project, coursework, or experience.
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 suits reviewers who want to follow experience, education, and skills in sequence.
Why This Format Works
- Experience and project achievements follow one reading path, keeping career evidence in sequence.
- Education and credentials remain part of the same ordered review alongside skills.
- Skills and tools can be read in context with the resume’s project evidence.
Best For
- A direct top-to-bottom review
- Sequential career and education details
- Readable project evidence
- ATS-friendly text flow
- Straightforward section navigation
Resume Keywords
- statistics
- data analysis
- Data science
- Logical reasoning
- generative AI
- Large language models
- Amazon SageMaker
- Python
- Computer Vision
- data visualization
#2 Simple Two Column Format Resume Example
Two side-by-side content areas give this resume a compact structure for readers who prefer to compare sections at a glance.
Why This Format Works
- Separate content areas let reviewers compare experience with supporting education and credentials.
- Skills and tools can occupy a distinct area without interrupting experience details.
- Project achievements remain easy to revisit alongside other resume sections.
Best For
- Side-by-side section review
- Compact supporting information
- Skills alongside career evidence
- Quick section comparison
- Balanced content density
#3 Plain One Column with Shaded Labels Resume Example
A one-column body with shaded labels marks section changes while keeping the resume’s content in a single reading sequence.
Why This Format Works
- Shaded labels distinguish experience, education, and skills without splitting the reading path.
- Clear section changes help reviewers return to project achievements during a later scan.
- A single content column keeps credentials and supporting details in reading order.
Best For
- Clearly marked resume sections
- Single-path reading
- Easy return to key sections
- Education and credentials in sequence
- A restrained visual structure
#4 One Column Format with Photo Right Resume Example
The right-side photo adds a visible identity cue, while the one-column body keeps resume sections in a direct reading order.
Why This Format Works
- The single reading path keeps experience and project achievements in a clear sequence.
- Education and credentials remain easy to locate within the main content column.
- Skills and tools can be reviewed without navigating between separate content areas.
Best For
- A resume with a right-side photo
- Direct section-by-section review
- Career evidence in one reading path
- Easy access to education details
- A visible personal identity cue
#5 Clean Two Column Sidebar Format Resume Example
A sidebar beside the main content gives this two-column format a clear way to separate supporting details from the central resume material.
Why This Format Works
- The sidebar separates supporting skills and credentials from experience details for clear section navigation.
- Project achievements stay distinct from education and other supporting information.
- Two content areas give reviewers a quick way to move between resume sections.
Best For
- Sidebar-based section organization
- Distinct supporting information
- Quick movement between sections
- Project evidence beside qualifications
- A clear content hierarchy
#6 Two Column Format Resume Example
Two columns provide parallel reading areas, helping reviewers move between the resume’s experience and supporting sections.
Why This Format Works
- Parallel content areas keep experience distinct from education and credentials during review.
- Skills and tools have room alongside career evidence rather than within its reading path.
- Separate areas help reviewers locate project achievements and supporting details.
Best For
- Parallel section review
- Experience beside supporting details
- Skills and tools in a separate area
- Multiple types of resume evidence
- A compact content arrangement
#7 Photo Header Two Column Format Resume Example
A photo in the header pairs with a two-column body, giving the identity area a distinct place above the resume content.
Why This Format Works
- The two-column body separates experience from supporting education and credentials.
- Skills and tools can be reviewed apart from project achievements in the main content.
- A distinct header keeps the photo separate from the resume’s section structure.
Best For
- A photo in the resume header
- Separate identity and content areas
- Side-by-side section review
- Supporting credentials beside experience
- A visible personal identity cue
Why Build Your Entry-Level Data Analyst / Data Scientist - Machine Learning Resume with ResumeInMinutes
ResumeInMinutes helps you arrange your skills, projects, education, and experience in a clear resume. You can review an image preview and open an example in the editor to explore its layout.
- ATS-friendly section structure
- Clear organization for skills and tools
- Space for projects and experience
- Readable achievement bullets
- Image previews for layout comparison
- Resume customization support
Use the resume to connect methods and tools with evidence. For example, describe how you compared model results, checked data quality, or used dashboards to make findings easier to understand.
See Also
- 33 Data Analyst / Data Scientist Resume Templates with Example 2026 (ATS-Optimized)
- 7 Entry Level Data Scientist/Analyst/Engineer Resume Templates with Example
- 33 Junior Data Scientist/Analyst Resume Templates with Example 2026 (ATS-Optimized)
- 33 Entry Level Machine Learning Engineer/Data Scientist Resume Templates with Example 2026 (ATS-Optimized)
- 33 Applied Machine Learning Scientist Intern Resume Templates with Example 2026 (ATS-Optimized)
- 33 Associate Data Scientist Resume Templates with Example 2026 (ATS-Optimized)
- 7 Data Scientist - Court Data Analytics Resume Templates with Example
- 7 Data Scientist, Entry Level Resume Templates with Example
- 7 Entry-Level Data Analyst / Data Scientist - Machine Learning Cover Letter Templates with Example
- 30+ Data Analyst / Data Scientist Cover Letter Templates with Example 2026
Frequently Asked Questions
Are these Entry-Level Data Analyst / Data Scientist - Machine Learning resume templates ATS-friendly?
The examples use familiar section headings and a clear structure to support scanning and ATS parsing. Include relevant terms such as Python, statistics, machine learning, and data visualization when they accurately describe your skills.
How can I compare the resume examples?
Review the image previews to see how each layout arranges resume sections. Open an example in the editor to inspect its structure and customize it.
What should an Entry-Level Data Analyst / Data Scientist - Machine Learning resume include?
Include a focused summary, education, relevant projects or experience, technical skills, and certifications when applicable. Use bullets to explain your analysis, tools, evaluation steps, and findings.
Which resume format works well for this role?
A simple one-column format can make headings and bullet points easy to scan. Choose a layout that gives enough space to show analytical work clearly and keeps important details in a logical order.
How can I show project experience on my resume?
State the project goal, the data or method you used, and what you delivered. For example, describe data preparation, model comparisons, dashboard work, or a report, and include specific results when you can support them.
Should I include a photo on my resume?
Include a photo only if it is customary or expected in your country, region, or industry. For U.S. applications, a resume without a photo is generally the safer choice.
