Computer Science CV Example

CV structure for computer science roles

A computer science CV follows a different order than most professions. Every applicant has the degree, so your differentiator is what you have built. Use this structure:

1. Contact details – include your GitHub profile and portfolio URL in the header. For a CS student with limited paid experience, a recruiter clicking through to working, well-documented repos is the strongest evidence of coding ability you can offer.
2. Personal statement – 3-4 lines stating your degree and classification (e.g. "First-Class BSc Computer Science"), your strongest technical area, and the kind of tech role you want. Tailor it per application rather than writing one generic statement.
3. Technical skills – group into scannable categories (Languages, Frameworks, Cloud/DevOps, Data, Concepts) rather than one undifferentiated list. Only list technologies you can discuss confidently for five minutes in an interview.
4. Experience – paid roles, internships, and placements. Foreground an industrial placement or summer internship as real experience. A 12-month placement is the one thing that justifies a CS grad CV running to two pages.
5. Projects – academic and personal projects fill the experience gap for a CS grad. Write each as: project name plus tech stack, a one-line GitHub link, a one-sentence purpose, your specific contribution, and a measurable outcome (user count, accuracy percentage, latency, deployment status).
6. Education – push to the bottom. List relevant degree modules (Machine Learning, Algorithms, Distributed Systems, Databases) tailored to the role. Include your final-year project or dissertation with its title, the technical problem it solved, and grade if strong. Drop irrelevant modules rather than listing every course. Omit A-levels and GCSEs unless genuinely exceptional.
7. Certifications and extras – AWS, Azure, or relevant professional certifications. Skip "references available on request" and use that space for another project or module list.

Mirror keywords from the job spec (e.g. "parallel programming," "machine learning," specific languages or frameworks) into your skills and project bullets. CS grad applications are ATS-screened at volume, and the matched technical terms are what surface your CV.

Writing achievement bullets for computer science roles

Avoid vague bullets like "Worked on the backend" or "Contributed to the codebase." For a CS grad, write action verb → what you built → quantified result. Vague technical descriptions are the top reason grad CVs read as generic.

The formula: [Action verb] + [specific technical contribution] + [measurable outcome].

Before and after examples

Before (vague): "Worked on the backend of a web application."

After (specific): "Built a Flask REST API serving 5,000 requests per day, cutting page load time by 40%."

Before (vague): "Helped improve system performance."

After (specific): "Optimised database indexing and query structure, reducing report generation time from 12 seconds to 3 seconds for datasets over 100k rows."

Before (vague): "Developed a machine learning model."

After (specific): "Trained a Random Forest classifier achieving 89% accuracy on a 50k-sample dataset, deployed via Flask API to serve real-time predictions."

Action verbs for computer science CVs

Use precise, technical verbs that reflect what you actually did:

• Building: Built, developed, implemented, designed, created, engineered
• Improving: Optimised, refactored, reduced, improved, increased, automated
• Deploying: Deployed, migrated, configured, integrated, launched
• Collaborating: Collaborated, contributed, led, mentored, reviewed
• Testing: Tested, validated, debugged, profiled, monitored

Education and certifications

Education section

For a CS graduate, push education to the bottom of your CV. Every applicant has the degree, so the differentiator is what you have built.

What to include:

• Degree title, classification, and university
• Graduation year (or expected graduation year)
• Relevant modules tailored to the role you are applying for. Citing a Machine Learning module supports credibility for an AI-focused application. Drop irrelevant modules rather than listing every course you took.
• Final-year project or dissertation: include the title, the technical problem it solved, and the grade if strong. This is often the most substantial piece of independent engineering a CS grad can point to, and it gives interviewers a concrete topic to dig into.

Example:

University of Manchester Bachelor of Science, Computer Science 2022–2025 | First-Class Honours (78% average) Relevant modules: Machine Learning, Algorithms & Data Structures, Distributed Systems, Databases, Software Engineering Final-year project: "Real-Time Sentiment Analysis of Social Media Streams" – built a Python pipeline using Kafka and TensorFlow achieving 84% classification accuracy on 10k tweets/hour (grade: 82%)

What to omit:

• A-levels and GCSEs unless genuinely exceptional (e.g. national awards, perfect scores)
• Every module you took. Tailor the list to the role.
• "References available on request" – use that space for another project or module.

Certifications

List relevant professional certifications in a dedicated section or under "Achievements." For computer science roles, certifications that matter include:

• Cloud: AWS Certified Solutions Architect, AWS Certified Developer, Microsoft Azure Fundamentals, Google Cloud Associate
• DevOps: Certified Kubernetes Administrator (CKA), Docker Certified Associate
• Security: CompTIA Security+, Certified Ethical Hacker (CEH)
• Data: TensorFlow Developer Certificate, Microsoft Certified: Azure Data Scientist Associate
• Agile: Certified ScrumMaster (CSM), Professional Scrum Master (PSM)

Only list certifications you have completed. Do not list "in progress" unless you have a confirmed exam date within the next month.