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Amazon Data Analyst Resume Examples

This article provides examples of resumes for Amazon Data Analysts, highlighting best practices and important skills to include.

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Brenna Goyette
Certified Professional Resume Writer, Career Expert

Published 9 min read

This article will provide readers with a step-by-step guide on how to write an effective resume for a Data Analyst position at Amazon. It will cover topics such as crafting a compelling summary, highlighting relevant experience, and emphasizing the skills needed to succeed in this role. Additionally, it will provide tips to help applicants stand out from the competition and land their dream job.

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Amazon Data Analyst Resume Example

Lupita Stice, Data Analyst

lupita.stice@gmail.com

(568) 568-4396

Portland, ME

Professional Summary

As a Data Analyst with over 1 year of experience, I have leveraged my strong analytical and problem-solving skills to develop and implement successful data analysis projects. I have a proven track record of creating data-driven strategies and solutions that have provided insights to assist in making better business decisions. I am adept at extracting data from various sources, manipulating and interpreting large sets of data, and visually communicating the results. Additionally, I am experienced in working with SQL and Excel to develop reports and dashboards, as well as identify data trends. I am a creative and strategic thinker with an eye for detail who is passionate about helping organizations use data to make better decisions.

Work Experience

Senior Data Analyst at MaineHealth, ME

Sep 2022 - Present

  • Developed and implemented a predictive analytics model that increased patient satisfaction scores by 10%, resulting in an estimated $1.2M annual cost savings for MaineHealth: Leveraging advanced statistical methods, I built a machine learning-based system to predict which patients were most likely to be dissatisfied with their care experience; this allowed the organization to proactively address potential issues before they became problems.
  • Streamlined data access across multiple departments of Mainehealth leading to improved performance efficiency: By designing and implementing automated scripts, processes and procedures related to database management systems (DBMS), I was able improve collaboration between teams while also reducing manual workloads associated with traditional ETL solutions. This resulted in 50% faster report generation times compared previous efforts.
  • Developed innovative dashboard solution enabling real time visibility into key operational metrics at all levels of the organization: Utilizing my knowledge on visualizations best practices along with software development skills such as HTML5/CSS3 & JavaScript frameworks like AngularJS & React JS ,I created dynamic dashboards allowing managers have immediate insight into current operations status without having need additional training or resources.

Data Analyst at Unum, ME

Jul 2022 - Aug 2022

  • Developed a predictive model to identify high-risk customers, resulting in an 8% reduction of customer attrition rate.
  • Designed and implemented a data warehouse that integrated disparate sources from the company’s ERP system into one centralized repository for faster reporting capabilities; this allowed Unum ME to save over $200K annually on IT costs.
  • Generated executive level reports detailing sales performance trends across all regions which enabled marketing teams to target their campaigns more effectively, leading to 25% increase in overall revenues within 6 months.

Education

Bachelor of Science in Data Analytics at University of Maine, Orono, ME

Sep 2017 - May 2022

Relevant Coursework: Data Management and Analysis, Database Design, Statistics and Probability, Machine Learning, and Data Visualization.

Skills

  • Data Mining
  • Statistical Analysis
  • Data Visualization
  • Machine Learning
  • Database Management
  • Business Intelligence
  • Problem Solving

Certificates

  • Cloudera Certified Professional: Data Analyst
  • Tableau Desktop Specialist

Tips for Writing a Better Amazon Data Analyst Resume

1. Highlight Your Data Analysis Skills: Make sure to list any data analysis skills you have on your resume, such as SQL, Python, R, Tableau, and Excel. Showcase any experience you have with data analysis, such as building predictive models or creating reports from large datasets.

2. Include Relevant Keywords: Amazon algorithms look for certain keywords when searching for resumes. Be sure to include these keywords in your resume, such as “data analyst”, “machine learning”, “big data” and “visualization”.

3. Showcase Your Experience: List any projects you have worked on that involve data analysis or machine learning. Include relevant details about the project like the size of the dataset and the results achieved.

4. Provide Examples of Your Work: If possible, provide examples of your work that demonstrate your data analysis skills and experience. This could be a dashboard you created using Tableau or a report generated from an Excel spreadsheet. These examples will show potential employers that you are capable of performing the job requirements successfully.

5. Use Action Verbs: Use strong action verbs throughout your resume to demonstrate your knowledge and capability in data analysis roles. Examples of action verbs include analyzed, developed, designed, created and implemented.

Related: Data Analyst Resume Examples

Key Skills Hiring Managers Look for on Amazon Data Analyst Resumes

When applying for a Data Analyst opportunity at Amazon, it is important to incorporate keywords from the job description into your application. This is because Amazon uses Applicant Tracking Systems (ATS) to screen and sort through applications. ATS are designed to scan for specific keywords related to the job opportunity and rank applicants accordingly. By incorporating relevant keywords from the job description in your application, you will be able to ensure that your application stands out from other applicants and that you are more likely to get chosen for an interview.

When applying for a data analyst position at Amazon, some of the common skills and key terms you may encounter include:

Key Skills and Proficiencies
Data MiningStatistical Analysis
Machine LearningData Visualization
Database ManagementData Modeling
Business IntelligencePredictive Analytics
R ProgrammingPython Programming
SQL QueryingExcel/Spreadsheets
Data Cleaning/WranglingReporting & Dashboarding
ETL (Extract, Transform, Load) ProcessesBig Data Technologies
Text MiningNatural Language Processing (NLP)
Time Series AnalysisForecasting & Optimization Techniques
A/B TestingAlgorithm Design

Related: Data Analyst Skills: Definition and Examples

Common Action Verbs for Amazon Data Analyst Resumes

It can be difficult to find the right action verbs to use on a resume, especially when crafting an Amazon Data Analyst Resume. It is important to use varied and specific verbs in order to make your resume stand out. Action words such as “analyzed”, “created”, and “implemented” are just a few examples of words that can be used to describe the tasks you have completed as a data analyst. Additionally, it is essential to choose words that accurately reflect the skills and accomplishments you have achieved in your role as a data analyst at Amazon. By including these action verbs in your resume, you will help yourself stand out from other applicants and demonstrate how you have contributed to Amazon's success.

To give you an advantage over the competition, we've created a list of powerful action verbs that can be used to strengthen your resume and secure your next interview:

Action Verbs
AnalyzedInterpreted
CollectedVisualized
ProcessedDeveloped
OptimizedAutomated
InvestigatedMonitored
ForecastedMined
AssessedStructured
IdentifiedReported
ExaminedEvaluated
ModeledCleaned
ImplementedDocumented

Related: What does a Data Analyst do?