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Written by Charlotte GraingerCharlotte Grainger

Data Scientist CV Examples & UK Templates

You’re a pro when it comes to analysing data and sharing your predictions. But how can you let a hiring manager know you have what it takes? Take a look at our data scientist CV example and writing guide for the insights you need.
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Data Scientist CV Examples & UK Templates
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You’re the brains behind the machine. Thanks to your nifty analysis and smart insights, the company is flourishing. Yes, you’re kind of a big deal. As a data scientist, you play one of the most important roles in any type of business. You offer problem-solving insights that could instantly change the course of the company. So, how can you put that on paper?

Writing an exceptional data scientist CV takes a certain finesse. You need to know what details to include and what to leave out. Luckily, we’ve got you covered. At Resume.io, we have the information you need to supercharge your job search. Our extensive library of expert-backed CV examples, along with handy writing guides, is a great place to start. 

If you’re ready to take the next step on the career ladder, we’ve got you covered. In the following writing guide — along with the data scientist CV example — we will touch upon: 

  • What a data scientist does including the daily duties and tasks
  • How to write a data scientist CV from scratch and which sections to include
  • Advice on selecting the right structure for your CV, plus a CV sample
  • Writing tips for each section (summary, work history, education, skills)
  • How to make sure your CV makes the right first impression.

What does a data scientist do?

Data scientists play a vital role in the modern business world. These savvy professionals analyse data sets and make informed predictions and insights. Looking at the available statistics and figuring out what they mean takes a strong scientific mind. It’s no easy feat. 

While the duties of each professional may vary depending on the company, the day-to-day tasks of this job role tend to include the following: 

  • Defining the right sets of data and understanding the variables
  • Pinpointing any issues within the data analytics and sharing the results
  • Ensuring that the data is always used accurately and legally in the business
  • Utilising models and algorithms to analyse the available data
  • Gleaning findings from these tests and using them to make predictions
  • Understanding the data and utilising it to discover business opportunities
  • Create reports that aptly share the findings of the data analytics
  • Clearly and concisely communicating the results and insights to business leaders

This high-level job is about problem-solving. You use the evidence you have been presented with — the data sets — to solve complex issues. Not only do you need a mind for numbers but you also have to have the ability to understand any potential biases that are in the data. Luckily, with the right training and qualifications, you can get the job done. 

Data scientists are not confined to one field. These professionals can use their skills across a wide selection of sectors including retail, scientific research, academia, health and fitness, information technology, finance, and governmental bodies. When you have gathered experience in this position, you may choose to dip your toe into another industry.

Statistical insight

How much do data scientists make?

The national average salary for a data scientist is £50,044, according to Glassdoor. However, this amount will vary depending on where in the United Kingdom you live. 

If you’re a London dweller, for example, the average salary is £55,373 for this position. Of course, you have to account for the higher cost of living in the capital here.

Aside from having an analytical mind and understanding data, you also need to be a people person. This job rests upon the foundation of solid working relationships. Before landing your next role, make sure you properly sharpen your communication skills. 

How to write a data scientist CV

You’ve sat down to write your data scientist CV — so where should you start? Since you’re used to working with formulas and structures, we’ve got just what you need here. Your application should include the following elements in this precise order: 

  • The CV header
  • The CV summary (aka profile or personal statement)
  • The employment history section
  • The education section
  • The CV skills section

You may not be a natural wordsmith. However, you need to take the right approach when writing your data scientist CV. Be sure to use a professional tone of voice. That means avoiding any chatty or colloquial language. Additionally, you should omit any jargon-heavy words. The first person reading your CV may not be up to date with the industry lingo. 

Research is vital when applying for a new role. While you may be tempted to use a one-size-fits-all CV, that will do you no favours. Hiring managers can spot an untailored CV a mile off and it may be enough to land you in the “no, thanks” pile. Do some research about the business to which you’re applying and edit your entire application accordingly. 

Keep in mind that the company may be using ATS screening software. Application Tracking Systems rank incoming CVs based on how well they fit the job specification. 

You’d have to be psychic to know exactly what they are looking for. However, you can get an idea by reflecting on the original job posting. Pick out any keywords you notice there. By including these in your data scientist CV, you may increase your chances of success. 

Looking for some more writing inspiration? Check out our related CV examples below: 

Choosing the best CV format for a data scientist

Recruiters expect to see a reverse chronological format on most CVs. For that reason, sticking to this structure is a good move. You won’t give the reader any surprises and they can quickly get the information they need. Of course, there are exceptions to the rule. 

If you are a career-changer or lack years of data science experience, you may want to opt for a functional CV format instead. That way, you can showcase your skills and education over your employment history. Look at our complete CV formatting guide for more details. 

CV header

The CV header is the top section of the document. It’s where the recruiter’s eyes first land on the page. Make sure that it is clear and easy for them to digest. This section should include your name, your position, and contact details. Don’t try anything too wild. Your aim is to ensure that the hiring manager can contact you if they like what they see. 

CV summary example

Unless you love writing, the CV summary is likely to be the most daunting part of the process. This freeform section consists of two to four lines about your professional worth. Before you get started, consider what your strengths are as a data scientist. What is likely to make the hiring manager sit up and say “this candidate is worth my attention”?

Space is valuable in this section so don’t waste it. You need to keep things short and snappy. To help you cut down this blurb, you can leave out any “I have,” “I previously” or “I will” openers. Instead, you can get straight in there with the important information. 

With each line, make sure that you are focussing on one core message. That may be your ability to create partnerships with leaders, your unique experience in the field, or where you see the industry going in the years to come. The more specific you are, the better.  

Adaptable summary CV sample

Versed in current advances in areas such as machine learning and statistics. Highly adept with tools, techniques and software for conducting statistical analysis and advanced computations. Forge partnerships with corporate leadership in advising on research and development of next-generation data science technologies. Advocate for data-driven corporate cultures.


Employment history sample

As we have mentioned, you will likely need to use the reverse chronological order when listing your education. Start with the most recent qualification you received and work your way back in time as you move down the page. You can use a header for your job title, company, and location. Beneath that, include your dates of employment.

To save space and make your CV easy to understand, use bullet points under each job that you list. Include your duties, daily tasks, and your most impressive accomplishments.

Adaptable employment history CV example

Senior Data Scientist at Tower York Financial Services, York 
February 2020 - Present

  • Formulate and implement credit risk models, including knowledge-based models and machine learning models.
  • Hire, train and manage high-performing data analyst teams.
  • Conceived and implemented credit policy strategies and processes from the ground up.
  • Designed and deployed decision support system for credit origination and credit risk management.


Analytics Manager at AQL, Leeds 
June 2017 - January 2020

  • Supervised team of three analysts in developing statistical modelling methods for enhancing efficiency of sales team.
  • Led development of tools for tracking and analysing all of the ongoing marketing campaign performance.
  • Oversaw statistical and data modelling to gain actionable business insights for strategic decision-making.
  • Designed predictive machine learning models.


Graduate Student Assistant, Statistics at University of York, York 
September 2016 - May 2017

  • Assisted Statistics professors of in assigning, monitoring and critiquing work of graduate students.
  • Worked closely with professors in developing lesson plans and creating / delivering content for classes such as Stochastic Processes and Deferential Equations.
  • Administered and graded exams, quizzes and daily lessons.

Data scientist CV education example

Next up, your education section takes a similar shape to your employment section. If you have been to university, then list that information here. As standard, you should include the name of the institute, the subject, the years that you attended, and your final mark. 

Have you completed any additional training? Don’t forget to include it. The more knowledge you have under your belt, the more valuable you will be to the business. 

Adaptable education CV example

Master of Science in Statistics, University of York, York 
September 2015 - May 2017 

Bachelor of Science in Applied Mathematics, Universitat de Barcelona, Barcelona 
September 2011 - May 2015


CV skills example

Adding the right skills to your CV shows a hiring manager where your expertise lies. You can use this section to really zero in on what you’re good at. With that in mind, here are some of the CV skills that recruiters expect to see in a data scientist’s application: 

  • Mathematics and statistical skills
  • Structured Query Language (SQL)
  • Machine learning and AI
  • Data visualisation
  • Customer analytics
  • Business strategising skills
  • Cloud computing
  • Predictive modelling

The above hard skills will do much of the heavy lifting when it comes to selling you as a professional. You can also sprinkle in some soft skills, such as communication, for good measure. Recruiters are looking for well-rounded candidates that can work well in teams. 

Adaptable skills section CV example
  • Deep Learning
  • Data Visualization
  • Predictive Modeling
  • Machine Learning
  • Probability Statistics
  • Customer Analytics
  • Microsoft Power BI
  • Data Visualisation

CV layout and design

Hiring managers are busy professionals and spend a matter of seconds looking at each CV. Hit them hard with an application that hooks their interest and looks the part. If you’re new to the realms of design, we have some expert layout tips to get things moving: 

  • Get the spacing right! Make sure that you have an equal amount of space between each CV section.
  • Keep the font plain. You need to ensure that the hiring manager can quickly and easily read your CV.
  • Take the formal approach. A minimal design style suits this type of CV and screams professional.
  • Mix and match design styles. You need to stick to one solid look and allow that to flow throughout here.
  • Make the font too big or small. As a golden rule, you should be using a 10-11 pt typeface for your CV.
  • Add in too much colour. You are applying for a data-driven role, not a creative industry one.

Worried about how to get the design on point? Use one of our field-tested CV templates to do all of the hard work for you. That way, you can focus on what truly matters: the content.

Key takeaways for a data scientist CV

  1. Working in data science takes an analytical mind and the right know-how.
  2. If you have what it takes to succeed, writing an effective data scientist CV will help you along the way.
  3. Adopt the right tone when writing your application. This is a professional process, and so your writing style needs to mirror that.
  4. Catch the recruiter’s eye for the right reasons. Avoid over-the-top CV designs and stick to something more formal for the best results.
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