Data Science Graduate CV example

If you’ve recently graduated and you’re looking to kickstart your career in data science, then you need to showcase your brand-new skills and qualifications with an eloquent CV.

But if you’re new to the job search it can feel a little daunting. That is why we’ve created this guide, to show you how to use your personal data to write a persuasive application.

We’ve also created a data science graduate CV example to inspire you further.

 

 

 

Data Science Graduate CV example

Data Science Graduate CV 1

 

This CV example showcases the optimal structure and format for your Data Science Graduate CV, providing a pleasant reading experience for busy recruiters.

It also demonstrates the skills, experience and qualifications you should emphasize in your own CV to increase your chances of landing job interviews.

 

CV builder

 

Data Science Graduate CV format and structure

If you focus purely on the written content of your CV but ignore the style and layout, your efforts could end up wasted.

No matter how suitable you are for the role, no recruiter wants to spend time squinting and trying to navigate a badly designed and disorganised CV.

Instead, make sure to organise your content into a simple structure and spend some time formatting it for ease of reading – it will ensure every recruiter and hiring manager can read your CV with ease.

 

How to write a CV

 

Tips for formatting your Data Science Graduate CV

  • Length: Even if you’ve got tons of experience to brag about, recruiters don’t have time to read through overly lengthy CVs. Keep it short, concise and relevant – a CV length of 2 sides of A4 pages or less is perfect for the attention spans in today’s job market.
  • Readability: Recruiters appreciate CVs that they can quickly scan through without trouble. Ensure yours makes the cut by formatting your headings for attention (bold or coloured fonts should do the trick) and breaking up long paragraphs into smaller chunks or short, snappy bullet points.
  • Design & format: While it’s okay to add your own spin to your CV, avoid overdoing the design. If you go for something elaborate, you might end up frustrating recruiters who, above anything, value simplicity and clarity.
  • Photos: Headshot photos aren’t required in a CV by most employers, but some creative and artistic industries like to see them. If you decide to include one, make sure you look smart and professional in the picture.

 

Quick tip: Creating a professional CV style can be difficult and time-consuming when using Microsoft Word or Google Docs. To create a winning CV quickly, try our quick-and-easy CV Builder and use one of their eye-catching professional CV templates.

 

CV formatting tips

 

 

CV structure

For easy reading, write your CV to the following CV structure:

  • Contact details – Make it easy for recruiters to get in touch with you by listing your contact details at the top of your CV.
  • Profile – A short and snappy summary of your experience and skills, showcasing what makes you a good fit for the position.
  • Work experience / career history – Note down all your work history, with your current position first, then working backwards.
  • Education – A short list of your academic background and professional/vocational qualifications.
  • Interest and hobbies – This is an optional section, which you can use to highlight any relevant hobbies or interests.

Now you understand the basic layout of a CV, here’s what you should include in each section of yours.

 

Contact Details

Contact details

 

Start off your CV with a basic list of your contact details.
Here’s what you should include:

  • Mobile number
  • Email address – It’s often helpful to make a new email address, specifically for your job applications.
  • Location – Share your town or city; there’s no need for a full address.
  • LinkedIn profile or portfolio URL – Make sure the information on them is coherent with your CV, and that they’re up-to-date

Quick tip: Delete excessive details, such as your date of birth or marital status. Recruiters don’t need to know this much about you, so it’s best to save the space for your other CV sections.

 

Data Science Graduate CV Profile

Grab the reader’s attention by kick-starting your CV with a powerful profile (or personal statement, if you’re a junior applicant).

This is a short introduction paragraph which summarises your skills, knowledge and experience.

It should paint you as the perfect match for the job description and entice recruiters to read through the rest of your CV.

 

CV profile

 

How to write a good CV profile:

  • Make it short and sharp: It might be tempting to submit a page-long CV profile, but recruiters won’t have the time to read it. To ensure every word gets read, it’s best to include high-level information only; sticking to a length of 3-5 lines.
  • Tailor it: The biggest CV mistake? A generic, mass-produced document which is sent out to tens of employers. If you want to land an interview, you need to tailor your CV profile (and your application as a whole) to the specific roles you’re applying for. So, before you start writing, remember to read over those job descriptions and make a list of the skills, knowledge and experience the employers are looking for.
  • Don’t add an objective: Leave your career objectives or goals out of your profile. You only have limited space to work with, so they’re best suited to your cover letter.
  • Avoid generic phrases: “Determined team player who always gives 110%” might seem like a good way to fill up your CV profile, but generic phrases like this won’t land you an interview. Recruiters hear them time and time again and have no real reason to believe them. Instead, pack your profile with your hard skills and tangible achievements.

 

Example CV profile for Data Science Graduate

1st Class Data Scientist Graduate with internship experience working on the development of data capture systems. Proficient in machine learning, data analysis, and predictive modelling supported by extensive knowledge of Python, R and SQL programming languages. IBM-Certified Database Associate adept at identifying inefficiencies in databases and producing conclusive reports.

 

What to include in your Data Science Graduate CV profile?

  • Experience overview: Demonstrate your suitability for your target jobs by giving a high level summary of your previous work work experience, including the industries you have worked in, types of employer, and the type of roles you have previous experience of.
  • Targeted skills: Make your most relevant Data Science Graduate key skills clear in your profile. These should be tailored to the specific role you’re applying for – so make sure to check the job description first, and aim to match their requirements as closely as you can.
  • Important qualifications: If the job postings require specific qualifications, it is essential to incorporate them in your profile to ensure visibility to hiring managers.

 

Quick tip: If you are finding it difficult to write an attention-grabbing CV profile, choose from hundreds of pre-written profiles across all industries, and add one to your CV with one click in our quick-and-easy CV Builder. All profiles are written by recruitment experts and easily tailored to suit your unique skillset.

 

Core skills section

Underneath your profile, write a core skills section to make your most relevant skills jump off the page at readers.

It should be made up of 2-3 columns of bullet points of your relevant skills.

Before you do this, look over the job description and make a list of any specific skills, specialisms or knowledge required.

Then, make sure to use your findings in your list. This will paint you as the perfect match for the role.

 

Core skills section CV

 

Important skills for your Data Science Graduate CV

Statistical Analysis – Using statistical methods and techniques for interpreting data and deriving insights.

Machine Learning – Maintaining knowledge of machine learning algorithms and their application in predictive modeling and data analysis.

Programming – Maintaining competency in programming languages commonly used in data science, such as Python, R, or SQL.

Data Visualisation – Creating clear and insightful visual representations of data using tools like Tableau, Power BI, or Python libraries like Matplotlib and Seaborn.

Big Data Technologies – Using big data platforms and tools like Hadoop, Spark, or Apache Kafka for processing large datasets.

Data Wrangling – Cleaning and preprocessing data to make it suitable for analysis.

Deep Learning – Understanding deep learning frameworks such as TensorFlow or PyTorch, especially for more advanced data science roles.

Natural Language Processing – Maintaining knowledge of techniques for processing and analysing textual data.

Data Mining – Extracting patterns and knowledge from large datasets using various data mining techniques.

Model Deployment and Maintenance – Understanding how to deploy machine learning models into production and maintaining them for accuracy and efficiency.

 

Quick tip: Our quick-and-easy CV Builder has thousands of in-demand skills for all industries and professions, that can be added to your CV in seconds – This will save you time and ensure you get noticed by recruiters.

 

CV builder

 

Work experience

Now that recruiters have a good overview of your skills and abilities, you need to jump into the detail of your career history.

Give them a more thorough insight into what you can do by creating a detailed list of your relevant experience.

Start with your current role, and work backwards through all the relevant positions you’ve held.
This could be freelance, contract or voluntary work too; as long as it’s related to the role you’re applying for.

 
Work experience
 

Structuring each job

If you don’t pay attention to the structure of your career history section, it could quickly become bulky and overwhelming.

Get in recruiters’ good books by creating a pleasant reading experience, using the 3-step structure below:

 
Role descriptions
 

Outline

Start with a solid introduction to your role as a whole, in order to build some context.

Explain the nature of the organisation you worked for, the size of the team you were part of, who you reported to and what the overarching purpose of your job was.

 

Key responsibilities

Next, write up a punchy list of your daily duties and responsibilities, using bullet points.

Wherever you can, point out how you put your hard skills and knowledge to use – especially skills which are applicable to your target role.

 

Key achievements

Round up each role by listing 1-3 key achievements, accomplishments or results.

Wherever possible, quantify them using hard facts and figures, as this really helps to prove your value.

 

Sample job description for Data Science Graduate CV

Outline

Selected out of a large group of applicants for a summer internship at Sanctum Data, a leading research centre specialising in the development and implementation of data capture systems.

Key Responsibilities

  • Developed and maintained SQL databases for data storage and retrieval
  • Worked as part of a team to develop predictive models using Python
  • Shadowed senior data scientists and contributed to research projects
  • Conducted exploratory data analysis to identify trends and insights

 

Quick tip: Create impressive job descriptions easily in our quick-and-easy CV Builder by adding pre-written job phrases for every industry and career stage.

 

 

Education section

Next up, you should list your education and qualifications.

This can include your formal qualifications (a degree, A-Levels and GCSEs), as well as sector-specific Data Science Graduate qualifications and/or training.

While school leavers and recent grads should include a lot of detail here to make up for the lack of work experience, experienced candidates may benefit from a shorter education section, as your work experience section will be more important to recruiters.

 

Hobbies and interests

The hobbies and interests CV section isn’t mandatory, so don’t worry if you’re out of room by this point.

However, if you have an interesting hobby, or an interest that could make you seem more suitable for the role, then certainly think about adding.

Be careful what you include though… Only consider hobbies that exhibit skills that are required for roles as a Data Science Graduate, or transferable workplace skills.

There is never any need to tell employers that you like to watch TV and eat out.

 

CV builder

 

An interview-winning CV for a Data Science Graduate role, needs to be both visually pleasing and packed with targeted content.

Whilst it needs to detail your experience, accomplishments and relevant skills, it also needs to be as clear and easy to read as possible.

Remember to research the role and review the job ad before applying, so you’re able to match yourself up to the requirements.

If you follow these guidelines and keep motivated in your job search, you should land an interview in no time.

Best of luck with your next application!