Data Analyst resume templates
Download a free resume template you can use when applying for Data Analyst jobs.
Download a resume template
Preparing to apply for a Data Analyst job? Take the guesswork out of resume building by downloading one of our free resume templates.Each template includes a formatted, easy-to-read resume outline that’s suitable for Data Analyst jobs. All you need to do is add your skills and experience.How you can get application-ready in three simple steps:
- Download one of our free resume templates.
- Tailor your resume with your skills, experience and contact details.
- Review your resume before saving it as a PDF. Then you’re ready to start applying with it!
Did you find this helpful?
Writing a resume for Data Analyst roles
The following information is a guide to the skills, experience and professional details you could include in your resume. Remember to always tailor your resume to your specific strengths and the requirements of the job you’re applying for.Technical skills to consider
SQL and database management
- Proficiency in writing and optimising SQL queries.
- Experience with database systems like MySQL, PostgreSQL or MongoDB.
Programming languages for data analysis
- Skills in Python and/or R for data manipulation and analysis.
- Familiarity with Pandas/NumPy libraries for data cleaning.
Data visualisation
- Expertise in creating visualisations using tools like Tableau or Power BI.
- Ability to use Matplotlib/Seaborn for static visualisations in Python.
Statistical analysis and machine learning
- Knowledge of statistical tools (for example, SPSS and SAS) for analyses.
- Familiarity with machine learning concepts and frameworks like Scikit-Learn.
Data cleaning and preparation
- Experience in cleaning and preparing data for analysis.
- Proficiency in Excel for data manipulation and analysis.
Soft skills to consider
Analytical thinking
- Ability to analyse complex datasets, draw meaningful insights and make data-driven decisions.
Communication
- Skills in conveying technical findings to non-technical stakeholders through clear and concise reports or presentations.
Attention to detail
- A detailed approach to data validation, cleaning and ensuring accuracy in analysis and reporting.
Problem solving
- A proven ability to successfully identify and resolve challenges or improve processes through data analysis.
Team collaboration
- Demonstrated experience in working collaboratively with cross-functional teams, as data analysis often involves cooperation with various departments.
Keywords to consider
Data analysisThis keyword signals that you have a fundamental understanding of the role and its core responsibilities.
SQLSQL is a critical skill for querying and managing databases, which is often a key aspect of data analysis.
Python/RThese programming languages are commonly used in data analysis for tasks such as data manipulation, statistical analysis and machine learning.
Statistical analysisDemonstrates your ability to apply statistical methods to draw meaningful conclusions from data.
Data visualisationMany stakeholders prefer visual representations of data. Proficiency in tools like Tableau or Power BI is valuable for effective communication.
Machine learningAs businesses increasingly leverage machine learning, having this keyword showcases your ability to work with advanced analytical techniques.
ExcelDespite more advanced tools, Excel remains widely used. Proficiency in Excel is often considered a baseline skill for data analysts.
Big data technologiesAs organisations deal with large volumes of data, familiarity with big data technologies like Hadoop and Spark can be a significant asset.
Data cleaning/data preprocessingCleaning and preprocessing data are crucial steps to ensure the accuracy and reliability of analysis results.
Business intelligence (BI) toolsBI tools help transform raw data into actionable insights. Experience with these tools is valuable for data analysts working to support decision-making within an organisation.
When writing your personal summary, you want to concisely communicate your skills, experience and what makes you a strong candidate for the position. Here's an example:
As a skilled data analyst with [X years] of experience, I excel in translating complex data into actionable insights using SQL, Python and Tableau. Proven expertise in statistical analysis and a commitment to data accuracy. Ready to contribute strong analytical skills to drive informed decision-making in your team.
These tips can help you write about your experience in a personalised, impactful way.
Tailor your experience to the jobCustomise your experience using keywords from the job description.
Focus on data-driven resultsHighlight achievements that showcase the impact of your data analysis work.
Use action verbsStart each bullet point with strong action verbs to make your experience more compelling.
Prioritise relevant experiencePlace the most relevant experience at the top of each role.
Include industry-specific keywordsUse relevant keywords to show you've researched the role and help your resume stand out to applicant tracking systems.
Keep it conciseAim for focused and concise statements of your experience. Avoid unnecessary details.
When hiring new employees, some companies use an Applicant Tracking System (ATS) to filter applicants. An ATS helps by collecting and organising job applications and reading through resumes to find the best matches.Creating a resume that’s easily readable by ATS involves adopting a simple and clear format to ensure compatibility with automated systems. Here are some practical tips you can apply to your resume:
- Use standard fonts and headings and avoid complex designs, graphics or tables that may confuse the ATS.
- Include relevant keywords from the job description throughout your resume, particularly in a dedicated skills section.
- Save your resume in a basic file format such as a PDF.
Did you find this helpful?
More tips to improve your resume and help you stand out
Once you’ve got your resume together, these articles have tips to help you refine it:
Did you find this helpful?
Skills and experience employers are looking for
Having the right skills and experience can make you an in-demand applicant. Data Analyst employers on SEEK are looking for job seekers with expertise in the following areas. SQL Query Language
Microsoft Power BI
Data Analysis
Python Programming
Tableau
Data Visualisation
Data Science
Analysis
Data Quality
Statistics
Source: SEEK job ads and SEEK Profile data
Did you find this helpful?
Latest Data Analyst jobs on SEEK
Be one of the first to discover these recently listed jobs, or browse all Data Analyst jobs on SEEK right now.Did you find this helpful?