Resume Guide

📄✨ A resume should quickly demonstrate your ability to analyze data, build models, and communicate insights to solve real-world problems. It should be tailored to a particular job/field.

Entry-Level Data Scientist

Entry-Level Data Analyst

Senior Data Scientist

Early/Mid-Career Data Engineering

Resume Sections & What to Include

This section outlines the key parts of a data science resume and what each one should contain to effectively showcase your qualifications.

Header

The header should clearly present your contact information and online professional profiles at the top of your resume.

Include

• ✅ Name.
• ✅ Email.
• ✅ City, State.
• ✅ LinkedIn address.
• ✅ GitHub address.
• ✅ Portfolio address (if applicable).

(Optional but powerful) Summary

A well-crafted summary can quickly highlight your most relevant skills, experience, or standout projects that match the job description.

Include if

• ✅ You have relevant experience or standout projects to spotlight immediately.
• ✅ You want to highlight tools, skills, or accomplishments that match the job posting.

Skip if

• ❌ You’re short on space and your resume is already aligned.
• ❌ You’re early in your academic career with little relevant experience.

Examples

• MS in Data Science student with hands-on experience in time series forecasting and machine learning; built a Python model that predicted weekly sales with 92% accuracy.
• Experienced in SQL, Excel, and Tableau; cleaned and visualized 200K+ row datasets to inform health equity policy decisions in a capstone project.

Avoid

• 🙅‍♂️ “Looking for a role where I can use my skills…”
• 🙅‍♂️ “Aspiring data scientist interested in machine learning…”

Education

List your academic background, degrees, and any relevant coursework or certifications related to data science.

Include

• ✅ Degree.
• ✅ School.
• ✅ Graduation Date.
• ✅ GPA (if 3.5+).
• ✅ Relevant coursework (include undergrad and grad).

Technical Skills

Include a targeted list of programming languages, tools, and technologies that demonstrate your technical capabilities.

Group by category

• ✅ Programming Languages: Python, R, SQL.
• ✅ Libraries: Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn.
• ✅ Tools: Git, Jupyter, Tableau, Excel.
• ✅ Concepts: Machine Learning, A/B Testing, Regression, NLP.
• ✅ Certifications: AWS certification, GCP certification, Azure certification.

Important!

Include only skills/tools you can demonstrate, and add them in the appropriate experience bullet points.

Project Experience

Highlight specific projects that show how you’ve applied data science skills to solve real-world problems.

Include

• ✅ 2–3 bullets pointsper project.

Project bullet-point formula

\text{Outcome} \to \text{Action} \to \text{Tool}

Examples

• Achieved 87% accuracy in loan default prediction by building random forest model using scikit-learn and cross-validation.
• Identified 15% drop-off in campaign engagement by cleaning and analyzing 10,000+ rows of marketing data using Python.

Experience

Detail your work history with action-oriented bullet points that emphasize outcomes, impact, and transferable skills.

Emphasis

• Data-related tasks and professional competencies.

Project bullet-point formula

\text{Outcome} \to \text{Action} \to \text{Tool}

Examples

• Improved user retention by 12% through A/B testing executed in Python and SQL.
• Guided $50K in nonprofit funding decisions through Tableau dashboards built from program data.

How to Use Generative AI Tools

Use AI tools (like ChatGPT or Claude) to support the thinking process behind resume writing, not to write the resume for you. AI is most effective when used as an assistant to help you analyze your experience, extract transferable skills, and reframe technical details for clarity.

Do

• ✅ Ask AI to analyze your resume against a job posting and identify gaps in language or emphasis.
• ✅ Share a job description and ask what keywords to include in your resume.
• ✅ Describe a project and ask AI to help surface the outcome or broader relevance (e.g., how your project saved time, improved a decision, or solved a real-world problem).
• ✅ Ask AI questions like “What skills are demonstrated by analyzing a large dataset in Excel?” or “How can I describe model evaluation in business terms?”

Don’t

• ❌ Don’t let AI inflate your impact or fabricate experiences.
• ❌ Don’t copy/paste bullet points written entirely by AI, as these often sound generic or exaggerated and may not reflect your voice.

Applicant Tracking System Tips

Learn how to format and optimize your resume so it is readable by applicant tracking systems (ATS).

Format	ATS Friendly?	Notes
.docx	Yes	Best overall option
.pdf	Sometimes	Use only if accepted by the application
.txt	Yes	Extremely plain; last resort
Google Docs	No	Must export as .docx or .pdf

Do

• ✅ Use standard headings: Education, Skills, Project Experience, Professional Experience.
• ✅ Use 10.5-12-point font (also important for readability by person).
• ✅ Use Microsoft Word to draft.
• ✅ Quick ATS Test: Copy your resume and paste it into Notepad. If text looks messy or missing, document likely cannot be read by ATS.
• ✅ Mirror terms from job description (e.g., A/B testing, regression, SQL).
• ✅ Use keywords in Skills, Project Experience, and Professional Experience.

Don’t

• ❌ Avoid tables, images, text boxes, columns.
• ❌ Don’t use headers/footers for contact info (skipped over by ATS).
• ❌ Don’t use | as a separator – use a bullet point or comma.
• ❌ Avoid synonyms unless they’re also listed.
• ❌ Don’t switch between Google Docs and Word – pick one format and stick with it (except for converting to .pdf)
• ❌ Don’t use online resume builders, Canva, ready-made templates.