Data Analyst Resume: Example and Tips
Data analysts are experts in processing and presenting data in ways that help organizations, such as helping businesses decide on which products should be developed, or what set of new customers should be targeted.
When it comes to a resume for this position, there’s no need to do heavy analysis — just use our expert tips and resume examples to build your own professional resume.
Featured resume example: data analyst
Name: BO SHEPARD
Address: City, State, Zip Code
Attentive Data Analyst offering sharp time management, organizational and assistance skills. Personable individual willing to work hard and take on any task. Pursuing full-time role involved in data analysis and research.
Company Name, City, State, FL 05/2018 – Current
- Research and transform information from raw data into an easily understood analysis that identifies trends and insights for the organization.
- Pinpoint a set of variables to evaluate and work with when deciding on the range of analysis and scope of information sought.
- Use a variety of sources inside and outside of the company to collect, aggregate and analyze data.
- Interpreted information from a series of database investigations to make predictions and recommendations for a company’s scope of work.
- Discussed results of database analysis with various members of management in an organization, and led staff members to realize the significance of the data.
- Discovered industry trends based on data collection methods and analysis strategies, and used the information to help the company make production and product adjustments to increase efficiency by 12 percent.
SUMMARY OF QUALIFICATION
- Expertise in computer programming languages such as Java, Python and C++, and database programs like Hadoop and MongoDB
- Outstanding use of problem-solving methods to help design the best strategies of measuring information and reviewing the results
- Excellent skills in analytical analysis and proven ability to read and interpret different points of data
- Documentation Management
- Report writing
- Research project support
- Quality assurance standards
- Database maintenance
- Data Entry
- Data Analysis
Bachelor of Science : Mathematics, City, State
Top 4 characteristics of a best-in-class data analyst resume
- Summary Keep your summary short and sweet, explaining your top skills and how you’ve applied them up to now. Think of this section as an “elevator pitch” that demonstrates what value you can add to the company. For example: “Thorough data analyst with a solid engineering background, passionate about improving the success of businesses.”
- Skills Your resume should feature a combination of technical and soft skills. Some of the more popular attributes recruiters look for include:
• Knowledge of database languages like Python or SQL
• Proficiency in Google Sheets or Microsoft Excel
• Knowledge of data visualization software like Qlik or Tableau
• Mathematical and statistical skills
• Leadership, problem-solving and decision-making skills
- Work history In this section, emphasize your achievements, giving specific details on how you’ve contributed to a company’s success. For example: “Used SPSS software to analyze data and conduct research for 2 major products, helping to increase sales by 14%.”
- Education A bachelor’s degree in business analytics, computer science, data science or a related field is usually a necessary requirement for a data analyst. Some other certifications and courses you should look to feature include:
• Bachelor of Science in Mathematics
• BBA, Business Statistics
• Open Certified Data Scientist
• Certified Analytics Professional
• Certification of Professional Achievement in Data Sciences
• Certified Data Management Professional
• Certified Health Data Analysts (for professionals in the healthcare sector)
• Intellipaat Big Data Hadoop Certification
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Find the right template for your resume
Make sure your own data looks its best — use one of these professionally-designed resume templates.
This popular design uses clean lines to differentiate sections, while the bold headings and subheadings make it easy to browse for information.
This layout uses elegant spacing to organize each section, while the unusual positioning of the job applicant name and contact information makes it stand out.
Do’s and don’ts for your resume
- Do only list tools/software that you have experience with Listing software or tools that you aren’t actually proficient in just misleads recruiters. Chances are you also won’t be able to explain how or in what context you’ve used these tools. Only list technologies that you are well-versed with, and show how you’ve deployed them in your work history.
- Do include internship experiences or relevant projects if you are a fresh graduate If you’re a first-time job seeker, include academic projects and internships in your work experience section — anything that demonstrates your aptitude and abilities for data analysis. Don’t forget to mention the tools you’ve used in your projects.
- Do highlight your relevant skills Focus on the most important skills that the job posting lists under “tasks” or “responsibilities”, such as Excel proficiency, or creating new reports within Tableau that drive efficiency. Match your own skills with these requirements, and then list them in your skills section, and display how you’ve used them in your work experience section (e.g., “Created reports within Tableau that led to improved processes and 15% increase in revenue”).
- Don’t go overboard with formatting Your data analyst resume should be crisp, clean and easy to read. Focus on your analytical and technical skills, qualifications and experience, rather than using flashy designs, fonts and colors. Using unusual layouts or fonts also runs the risk of confusing recruiters, as well as applicant tracking systems (ATS) that scan your resume to find the right data.
- Don’t lie The age-old adage “honesty is the best policy” holds very true for resumes. Lying about your skills, experience or educational qualifications can have major consequences if you’re exposed. If your skills or experiences don’t match up exactly with what the job requires, find ways to present them that suggest you’re capable of fitting in, or state in your summary that you can build on your foundation and pick up new skills quickly.
- Don’t share confidential information Don’t share privileged information from your previous jobs, especially if it comes to proprietary data or new technological developments. You should also stay away from sharing personal confidential information, such as your religious and political leanings. Limit any info about yourself to skills and experiences related to data analyst work.