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.
Table of Contents
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
See Why My Perfect Resume is a 5-Star Resume Builder
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.
This professionally-styled template uses subtle dotted lines to separate each section, while the use color resume fonts for the job seeker name and section headings place the focus on important info.
Visit our resume template page to choose from over two dozen more free layouts.
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.
Data analyst resume FAQ
- 1. What are the skills you should emphasize for this specific job?
- 2. What are some examples of training and certifications that fit this specific resume?
- 3. How should you format your resume?
- 4. How should you craft your resume if you’re looking to take the next step forward in your career?
1. What are the skills you should emphasize for this specific job?
Feature technical and soft skills in equal measure, including some of the following popular attributes:
- Data cleaning and preparation
- High level of mathematical ability
- Creating data visualizations
- Presentation skills along with written and oral communication skills
- Knowledge of the domain
- Problem-solving skills
- Knowledge of statistical programming languages such as SQL, Oracle, Python
- Interpersonal and teamwork skills
- Ability to analyse and interpret data
- Accuracy and attention to detail
- Machine learning
- Proficiency in Microsoft Excel
- Data reporting
- Predictive analysis
- Optimization and heuristics
- Developing risk simulations and operational analysis
2. What are some examples of training and certifications that fit this specific resume?
Certified professionals are very much in demand in the data science industry. Some certifications that will enable you to stand out from the crowd and enhance your key skills include:
- Intellipaat Big Data Hadoop Certification
- Cloudera Certified Professional
- MCSE Certification in Data Management and Analytics by Microsoft
- Hortonworks Hadoop Certification
- Open Certified Data Scientist
- MongoDB Certified Developer Exam
- Certification in EMC Data Science and Big Data Analytics
- SAS Certified Data Scientist
- Data Science Council of America certification
- Oracle Business Intelligence Certification
- Mining Massive Data Sets Graduate Certification
- Certification of Professional Achievement in Data Sciences
3. How should you format your resume?
Choose your resume format based on these guidelines:
- Data analysts with a lot of experience should use the chronological format, which features an extensive work history section.
- If you have limited experience, but have the required skill sets and qualifications, use a functional format, in which you can present your skills in different categories (e.g., technical skills, soft skills), along with highlights from your academic training.
- The combination format is a hybrid of the chronological and functional formats, and highlights both your relevant experience as well as skills. Use this format if you have a few years of experience, or are coming from a different career field, but have transferable skills and experiences you can feature.
4. How should you craft your resume if you’re looking to take the next step forward in your career?
Keep looking to improve your analytical capabilities to advance your career. Formal education, boot camps, online courses and advanced degrees will help you obtain greater knowledge of important areas such as machine learning, neuro-linguistic programming (NLP) and supervised/unsupervised learning. Also look to expand your expertise into areas that are of prime importance to your employer, such as healthcare, biology, stock markets or advertising.
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