Data science is one of the most in-demand and competitive fields today. Whether you're just starting out as a fresher or transitioning from another tech role, having a polished and targeted resume can make all the difference in catching the attention of hiring managers.
This article provides a real, professional-quality data science resume sample, along with strategic writing advice tailored specifically for the industry. Let’s explore how to craft a standout resume that truly reflects your analytical abilities, technical skills, and project experience.
REALISTIC DATA SCIENCE RESUME SAMPLE (FRESHER TO MID-LEVEL)
Name: Rohan K.
Phone: +91-90000-12345
Email: rohank.ds@email.com
Location: Bengaluru, India
LinkedIn: linkedin.com/in/rohan-ds
PROFESSIONAL SUMMARY
Detail-oriented and results-driven Data Science professional with hands-on experience in Python, SQL, and machine learning techniques. Proficient in building data pipelines, performing exploratory data analysis, and delivering actionable insights. Adept at working with cross-functional teams to solve complex business problems using data-driven approaches. Eager to contribute analytical expertise to innovative data science teams.
SKILLS
Programming: Python, R, SQL
Tools: Jupyter Notebook, Tableau, Power BI
Libraries: Pandas, NumPy, Scikit-learn, Matplotlib
Machine Learning: Regression, Classification, Clustering
Databases: MySQL, PostgreSQL
Data Wrangling, EDA, A/B Testing
Cloud: Google Colab, AWS (basic)
EDUCATION
Bachelor of Technology in Computer Science
SRM Institute of Science and Technology, Chennai
Graduated: 2023 | CGPA: 8.4/10
CERTIFICATIONS
IBM Data Science Professional Certificate – Coursera
Google Advanced Data Analytics Certificate – Google/Coursera
PROJECTS
1. Customer Churn Prediction
Tools Used: Python, Scikit-learn, Pandas
Developed a machine learning model using logistic regression and random forest to predict telecom customer churn with 85% accuracy.
Conducted exploratory data analysis to identify key churn indicators.
Presented insights using Tableau dashboards.
2. Sales Forecasting for Retail Chain
Tools Used: Python, ARIMA, Excel
Built time-series forecasting models to estimate monthly sales across regions.
Improved forecast accuracy by 20% over previous benchmarks.
Automated reports for real-time updates to the sales team.
INTERNSHIP EXPERIENCE
Data Science Intern
InfiTech Analytics, Remote | Jan 2023 – April 2023
Assisted in cleaning and preprocessing large datasets for client dashboards.
Built classification models for lead conversion prediction.
Created automated weekly insights reports using Python and Google Sheets API.
EXTRA-CURRICULAR ACTIVITIES
Data Science Club Member – Led weekly ML coding challenges.
Published 3 medium articles on beginner-friendly data projects.
TIPS TO WRITE A GREAT DATA SCIENCE RESUME
Highlight Technical Skills Clearly: Break down your skills by categories—programming, libraries, visualization, etc.—so recruiters can easily scan.
Showcase Real Projects: Use metrics and results wherever possible to demonstrate impact. Hiring managers love numbers.
Use Keywords from the Job Description: Tailor your resume to include exact phrases like "data wrangling," "predictive modeling," or "SQL querying."
Keep It One Page (for Freshers): Unless you have extensive experience, one page is ideal. Focus on the most relevant work.
Don’t Skip the Summary: A short, sharp summary at the top gives recruiters context before diving into your details.
FAQ ABOUT DATA SCIENCE RESUMES
Q1: What should a fresher include in a data science resume?
Focus on projects, certifications, and technical skills. Highlight hands-on experience, even if it's through personal or academic projects.
Q2: Should I include soft skills in my data science resume?
Yes, but briefly. Mention skills like communication, teamwork, and problem-solving, especially if you’ve worked in collaborative environments.
Q3: How do I make my data science resume ATS-friendly?
Use clear section headers, standard fonts, and incorporate keywords from the job listing. Avoid overly styled or image-heavy resumes.
Q4: Is it necessary to add GitHub or portfolio links?
Absolutely. Sharing your GitHub or a portfolio link adds credibility by showcasing your code and real project contributions.
With the right format, strategic keywords, and real examples, your resume can open doors to exciting data science roles. Use this guide to confidently present your skills and start getting interview calls.
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