Data Analyst Resume Samples & Templates

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Data Analyst Resume Summary Samples

Learn how to write a data analyst resume summar with these examples:

Data Analayst Resume Summary

Working as data analyst on energy department of ACME. Responsible for research and development to provide comprehensive database coverage on life-cycle, regulatory compliance, availability and cross references for energy consumption across North America.

Data Analyst Resume Summary Example

Created, improved, and maintained multiple data models for the insurance industry for Fortune 500 companies. Helped these companies save a total of $32B by leveraging state of the art fraud detection models.

Related: Our guide on how to write a resume summary.

Data Analyst Resume Experience Examples

Data Analyst Resume Experience

Data Analyst 2019-Present

• Data pre-processing and Data visualization for in-house industrial projects. Datasets were in formats ranging from time-series data to Images and applied computer vision Algorithms for sharpening Images, clearing outliers, augmenting data for creating good quality datasets.
• Applied Deep Learning algorithms on the clean image datasets for the classification problems, comparing multiple machine learning algorithms and finding relevant results with the guidance and support of my supervisor who was specialized in domain-relevant knowledge. Presented application of deep learning for in-house industrial projects from a business perspective.

Lead Data Analyst Resume Experience

Lead Data Analyst

• Analyze performance insights from 350+ sources.
• Map the users' user behavior, product metrics, and conversions statistics on ACME app and web.
• Perform Root Cause Analysis (RCA) to identify failure points and highlight corrective measures to regain business growth.
• Lead analyst for reporting and recommendations to cross functional stakeholders

Data Analyst Intern Work Experience

Data Analyst Intern 2014-2015

• Created reports and dashboards by extracting data from data sources, then performed ETL and data normalization.
• Help management and business users make important decisions of their business on the underlining data.
• Maintain large databases and used statistical techniques to collect, analyze, and interpret data from customers and partners.
• Presents data in the form of charts, graphs, and tables for immediate reference.
• Identify and report on data issues, and pro-actively participate in team meetings with manager.