Data Science CV Template, Example, & Writing Guide for 2024

Ensure your CV format is structured to best highlight your unique experience and life situation.

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How to write a data science CV

Before you begin writing, make sure you know how to write a CV in a way that best emphasises your strengths.

Data scientists analyse data to solve problems. So, to land a job in this field, begin by using your problem-solving skills to write an outstanding CV.

A well-crafted data science CV showcases your industry-specific skills, experience, and accomplishments to convince employers that you’re the most suitable candidate.

Here are three tips for creating a job-winning CV that lands you more data science interviews:

1. Add programming languages and software to your skills

Data scientists help inform business decisions by identifying trends and patterns in large amounts of data. Employers look to hire the best candidates with relevant hard skills and soft skills for this role. So you should add these skills to your CV.

Hard skills, which are abilities learned through practice and education, show your ability to deliver results in the workplace. For instance, your expert knowledge of programming languages like Python and R is valuable in data cleaning and manipulation, and analysis.

Or if you’re an expert in regression analysis, you should mention it on your CV to show you can establish a relationship between two data points to predict a company’s sales and understand supply and demand.

Other essential hard skills to include in your data science CV to demonstrate your expertise in the field include:

• statistical software (SPSS, MATLAB, Microsoft Excel)
• database management software (MySQL, Microsoft Access, JSON)
• data visualisation tools (Google Charts, Tableau, Infogram)
• machine learning
• big data frameworks

Even though data science mainly requires technical knowledge and skills, you’ll also need some soft skills to perform your duties properly in the field. Soft skills are personal attributes that show your ability to interact effectively and harmoniously with others in the workplace.

For instance, curiosity will help you go beyond initial assumptions to discover solutions to problems and deliver higher-quality insights from data sets.

Here are more soft skills to add to your data science CV to stand out from other candidates:

• Leadership skills
• Critical thinking skills
• Teamwork
• Storytelling
• Adaptability
• Communication skills

Ensure you mention these skills in the personal statement, work experience, and key skills sections on your CV. But avoid stuffing too many skills in one section by including only those relevant to the data science job posting.

2. Write a compelling, data-rich personal statement

Your target employers are probably busy sorting large data sets. As a result, they can’t carefully read each of the many job applications they receive. Ensure your job application is one of the few they read all the way through by writing an attention-grabbing CV personal statement.

A personal statement is a section at the top of your data science CV where you introduce yourself and your professional background. This paragraph should concisely summarise your skills and experiences in 3–5 sentences.

This section may seem tricky to write. But with the tips below, you can craft a compelling personal statement for your data science CV:

• Mention your number of years of experience as a data scientist and summarise your relevant skills
• State the statistical software and programming languages you’re most familiar with
• Include any licenses, certifications, and degrees you hold
• Describe your data science specialities
• Indicate how you intend to apply your expertise to make an impact at your target company

Here’s an example of an impactful data science CV’s personal statement:

3. Use metrics to prove your ability as a data scientist

Your data science CV’s work experience section should feature data to emphasise your measurable impact on profits and percentages. Quantifying your experience shows your verifiable accomplishments and contributions, highlighting the value you’ll bring to your target company.

Here’s how a data science job candidate used hard numbers to show their achievements in their CV’s work experience section:

• Designed and implemented a data model for the HR department that increased employee retention by 60%
• Collaborated with 3 colleagues by reviewing data and writing 20+ reports to provide key stakeholders with required improvements
• Discovered frequently ordered unsuccessful stock that caused the company to lose profits and presented detailed findings to executives, resulting in saving the company £500,000 each year

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