Data Analyst Resume Template Example

As businesses continue to use data for decision-making, they are looking to analysts to help them track and understand their metrics. Although the demand for data experts is high, you’ll need a resume that demonstrates an ability to filter, extract, and transform information into actionable strategies. This guide will help you create a data analyst resume that communicates this expertise while featuring your top career highlights.

How To Write a Data Analyst Resume

A resume template will help you organize your professional history by providing a structured outline for your writing. Here’s a quick overview of the sections to include in your data analyst resume:

  • Contact information
  • Profile
  • Key skills
  • Professional experience
  • Education and certifications

Contact information

Provide all the data hiring managers need to contact you for an interview. That includes your full name, phone number, email address, and location. Verify your information is current to avoid any miscommunication.

Also, include links to online professional profiles like GitHub and LinkedIn. According to recent stats, professionals with a complete LinkedIn profile increase their odds of landing an interview by 71%.

Example:

Your Name
(123) 456-7890
[email protected]
LinkedIn | Portfolio
City, State Abbreviation Zip Code

Profile

Your profile is like a data story – a brief, impactful summary to engage readers and draw them into your resume. To write a strong profile, pull together your most compelling professional data and present it in about two to three sentences. Include your job title and years of experience, then grab a few keywords from the job description and work them into your paragraph.

Example

Meticulous data analyst with over eight years of experience in e-commerce and online retail. Skilled in analyzing website data, customer behavior, and sales patterns. Track record of driving online sales through data-driven optimization and collaboration. Leverages tools like Google Analytics, Python, and Tableau and translates complex data findings into actionable strategies.

Key skills

Both hard skills and soft skills are essential for your job as a data analyst. Not only are you using complex techniques and software programs, but you must be able to communicate effectively with people outside the tech realm.

The technical skills you include on your data analyst resume will vary depending on your industry, so always defer to the job description of the position you’re applying for. What skills do you have that match the company’s needs? Prioritize these skills first and then add any others you know are relevant to the role.

Common hard and soft skills for data analysts

Hard Skills Soft Skills
Big data technologies (Hadoop, Spark, Hive) Adaptability
Data cleaning and preprocessing Analytical thinking
Data mining Attention to detail
Data visualization tools (Tableau, Power BI, Matplotlib) Collaboration
Database management (MySQL, PostgreSQL, MongoDB) Communication
Excel and spreadsheets Curiosity
Machine learning Emotional intelligence
Programming languages (Python, R, SQL) Leadership
Statistical analysis Storytelling
Data warehousing Time management

Resume writer’s tip: Use strong action verbs

As a data analyst, you know the key to an effective data story is compelling graphics, text, and presentation. Similarly, your resume should use engaging language to make it easy for the reader to understand what you’re communicating. Action verbs can help you do this. Use words like those below to start each bullet point in the professional experience section of your data analyst resume:

  • Analyzed
  • Automated
  • Conducted
  • Designed
  • Diagnosed
  • Executed
  • Extracted
  • Implemented
  • Interpreted
  • Modeled
  • Optimized
  • Streamlined
  • Synthesized
  • Validated
  • Visualized

Professional experience

Create a results-driven professional experience section by painting a picture of your job duties and achievements with action verbs and brief descriptions. This is where you get to put your data analysis skills on display, using bullet points to describe each accomplishment concisely.

For example, describe the results you’ve achieved through precise data preprocessing or demonstrate your mastery of programming languages like Python and SQL for data extraction and manipulation. Show hiring managers what they can expect if they hire you.

Example:

Data Analyst, Maggie’s Fashion, Orlando, FL
March 2018 – present

  • Developed a real-time dashboard for monitoring website traffic and user behavior, leading to a 13% boost in online engagement and $300,000 in additional revenue
  • Created a recommendation engine for cross-selling and upselling products
  • Utilized web analytics tools, such as Google Analytics and Adobe Analytics, to gain insight into key performance indicators (KPIs) for a 20% improvement in the online shopping experience
  • Conducted in-depth social media sentiment analysis to gauge customer satisfaction and feedback

Resume writer’s tip: Quantify your experience

Present career accomplishments with more than just a description by using numbers to quantify your experience. Performance metrics, percentages, and dollar amounts help hiring managers visualize your contributions. The value you can bring to their company becomes tangible. So, instead of giving vague descriptions of your role, get specific with numbers.

Do

  • “Collaborated with the merchandising team to identify underperforming product categories and implemented pricing and assortment adjustments, resulting in a 9% revenue increase”

Don’t

  • “I was responsible for working with the merchandising team to change prices and increase sales.”

Resume writer’s tip: Tailor your resume for each application

Demand for data analysts and data scientists is high, but you’ll still need an outstanding resume to land the best jobs. While it may be tempting to create one master resume to send out to each job application, this can ultimately work against you. You need to customize your document for each position.

Just like you can use data to optimize business performance, you can utilize keywords to optimize your resume. Study each job description and match your skills to the specific requirements. Then, update your resume by adding keywords to suit the position you’re applying for.

Resume writer’s tip: Highlight your leadership capabilities

Even if you’re not applying for a management role, leadership is a great skill to feature on your resume. Employers value someone who can take initiative. They want a data analyst who can step in as a project leader or solve a problem that stumped the team.

Throughout your professional experience section, highlight moments that show your ability to lead. For example, maybe you trained a group of junior analysts or took the time to implement an automated reporting system. Mention these things in your resume and demonstrate to hiring managers that you have a proactive growth-oriented approach.

Resume writer’s tip: How to choose the best resume format

Transforming raw data into valuable business insights requires a unique set of skills, making the combination resume a great choice for a data analyst resume. This format presents your skills closer to the top of your document, highlighting their significance above professional experience and education.

Hiring managers can capture your practical qualifications immediately. Then, they can go on to explore your work history, formal training, and certifications that will bolster your eligibility for the role.

What if you don’t have experience?

If you’re fresh out of college or have only worked on personal projects, you can still create a powerful resume. You’ll just need to get creative with how you order your sections and present information.

Put the focus instead on your education and potential certifications. You can include these higher up on your resume and elaborate on relevant courses.

If you’ve participated in volunteer work or significant academic projects, you can instead create a general “Experience” section. Just like in a professional experience section, you would highlight the accomplishments achieved and tasks performed in these instances.

Education and certifications

Prove you meet the job’s educational requirements by including all relevant academic experience and additional credentials. Most data analyst positions require at least a bachelor’s degree but include any other higher levels of education if you have them.

Certifications in programming languages and specific software should also be included. Even if they’re not required for the job, this shows hiring managers you took the initiative to get certified.

Example

Education

Master of Science (M.S.) Data Analytics, September 2011 – June 2013
Central Michigan University, Mount Pleasant, MI

Certifications

  • Certified Data Analyst (CDA), IABAC, 2013
  • Tableau Desktop Specialist, 2014

Data Analyst Resume Template Text Example

Your Name

(123) 456-7890
[email protected]
LinkedIn | Portfolio
City, State Abbreviation zip code

Profile

Meticulous data analyst with over eight years of experience in e-commerce and online retail. Skilled in analyzing website data, customer behavior, and sales patterns. Track record of driving online sales through data-driven optimization and collaboration. Leverages tools like Google Analytics, Python, and Tableau and translates complex data findings into actionable strategies.

Key Skills

  • Customer behavior analysis
  • Market segmentation
  • Predictive modeling
  • Presentation and communication
  • Python, AdWords, SQL, Excel
  • Sales forecasting
  • Statistical modeling

Professional Experience

Data Analyst, Maggie’s Fashion, Orlando, FL
March 2018 – present

  • Developed a real-time dashboard for monitoring website traffic and user behavior, leading to a 13% boost in online engagement and $300,000 in additional revenue
  • Created a recommendation engine for cross-selling and upselling products
  • Utilized web analytics tools, such as Google Analytics and Adobe Analytics, to gain insight into KPIs for a 20% improvement in the online shopping experience
  • Conducted in-depth social media sentiment analysis to gauge customer satisfaction and feedback

Data Analyst, Variety Apparel Co., Tampa, FL
November 2015 – April 2018

  • Carried out A/B tests for e-commerce platforms to increase conversion rates by 12%
  • Utilized advanced clustering techniques to segment the customer base and tailor marketing campaigns
  • Collaborated with the merchandising team to identify underperforming product categories and implemented pricing and assortment adjustments, resulting in a 9% revenue increase
  • Leveraged customer purchase history and market trends to optimize recommendations

Education

Master of Science (M.S.) Data Analytics, September 2011 – June 2013
Central Michigan University, Mount Pleasant, MI

Bachelor of Science (B.S.) Mathematics, September 2006 – June 2010
University of Michigan, Ann Arbor, MI

Certifications

  • Certified Data Analyst (CDA), IABAC, 2013
  • Tableau Desktop Specialist, 2014