Data Analytics Project Manager Resume Example & Writing Guide

Use this Data Analytics Project Manager resume example and guide to improve your career and write a powerful resume that will separate you from the competition.

Data analysts and data scientists use their knowledge of statistics and analytical thinking to analyze data and identify patterns, trends, and other useful information. Data analysts tend to focus on identifying opportunities and solving problems with data while data scientists tend to focus more on building new products and services using data-driven solutions.

As a data analyst or data scientist, you’re probably used to working with large volumes of data. But when it comes time to write your resume, it can be challenging to figure out how to present all that information in a way that’s both impactful and concise.

Follow these tips and example resume to write a data analytics project manager resume that hiring managers will love.

Michael Garcia
Chicago, IL | (123) 456-7891 | [email protected]

Experienced data analytics project manager with a demonstrated history of working in the information technology and services industry. Skilled in data management, business analysis, and process improvement. Excels at leading teams to deliver projects on time and within budget.

Northwestern University Jun '16
M.S. in Analytics and Data Science
University of Illinois at Urbana-Champaign Jun '12
B.S. in Mathematics and Statistics
Company A, Data Analytics Project Manager Jan '17 – Current
  • Managed a team of data analysts to deliver over 100 projects for the company’s largest client, including predictive modeling and optimization of marketing spend across all channels.
  • Developed an automated reporting tool that reduced project delivery time by 50% and increased efficiency by 20%.
  • Created dashboards using Tableau to track key performance indicators (KPIs) such as revenue per customer, lifetime value, acquisition cost, etc., which were used at executive level in weekly business reviews.
  • Analyzed user behavior on the website using Google Analytics and identified opportunities for A/B testing new features or landing pages resulting in a 10% increase in conversion rate within 6 months.
  • Built a machine learning model to predict whether customers would churn based on their usage patterns and account history with 80% accuracy saving the company $1M+ annually through targeted retention campaigns before leaving due to relocation –
Company B, Data Analytics Project Manager Jan '12 – Dec '16
  • Led the development of a data warehouse and business intelligence platform to support analytics for marketing campaigns
  • Managed all aspects of projects, including scope definition, requirements gathering, design and testing, deployment and post-deployment activities
  • Developed an automated system that improved customer service by identifying trends in ticket submission patterns
  • Spearheaded the implementation of a new data collection process using web scraping tools to improve reporting accuracy
  • Conducted regular project status meetings with stakeholders to ensure on-time delivery and quality results
Company C, Data Analyst Jan '09 – Dec '11
  • Analyzed data to identify trends and patterns that could be used to improve business operations.
  • Created reports and presentations to communicate findings to decision-makers.
  • Developed and implemented data-driven solutions to improve efficiency and accuracy.
  • Certified in Data Management
  • Certified Analytics Professional
  • Certified Business Intelligence Professional

Industry Knowledge: Data Analysis, Data Modeling, Data Visualization, Data Mining, Business intelligence, Business Analytics
Technical Skills: R, Python, SQL, Tableau, Microsoft Office Suite, Excel, PowerPoint
Soft Skills: Communication, Leadership, Problem Solving, Adaptability, Teamwork, Project Management

How to Write a Data Analytics Project Manager Resume

Here’s how to write a resume of your own.

Write Compelling Bullet Points

When it comes to data analytics project management, it’s important to demonstrate your ability to manage large, complex projects. And the best way to do that is by using specific examples from your past work.

So rather than saying you “managed projects,” you could say that you “managed $10M data analytics project for major retailer, ensuring on-time delivery of 200+ reports and data sets for more than 200 users.”

Notice how the second bullet point is much more specific and provides more detail about the project itself as well as the outcome? That level of detail will help hiring managers understand how well you can manage large projects and whether you’re the right fit for their organization.

Identify and Include Relevant Keywords

When you apply for a data analytics project manager role, your resume is likely to be scanned by an applicant tracking system (ATS) for certain keywords. ATS programs rank resumes based on the number of relevant keywords that are found in the job description. If your resume doesn’t include enough of the right keywords, your application might not make it past the initial screening process.

To increase your chances of getting an interview, use this list of keywords as a guide when writing your resume:

  • Data Analytics
  • Tableau
  • Data Science
  • Python (Programming Language)
  • Machine Learning
  • SQL
  • R (Programming Language)
  • Analytics
  • Databases
  • Microsoft Power BI
  • Data Visualization
  • SAS
  • Data Mining
  • SQL Server
  • Business Analysis
  • Statistical Modeling
  • Business Intelligence (BI)
  • Git
  • JavaScript
  • Microsoft SQL Server Reporting Services (SSRS)
  • Data Modeling
  • Big Data
  • Data Warehousing
  • Analytics Project Management
  • Data-Driven Decision Making
  • Requirements Analysis
  • Business Analytics
  • Software Development Life Cycle (SDLC)
  • Data Science Tools
  • Tableau Software

Showcase Your Technical Skills

As a data analytics project manager, you will be responsible for overseeing the development and implementation of data analytics projects. This will require you to be proficient in a variety of software programs and systems, including data mining, machine learning, and modeling. Additionally, you will need to have a solid understanding of big data concepts and platforms like Hadoop, Hive, and Spark.

In order to be successful in this role, you will need to have strong technical skills. Be sure to list any relevant programs, systems, and methodologies that you are familiar with on your resume. Indicating your level of expertise for each will show potential employers that you are a valuable asset.


Food Safety Auditor Resume Example & Writing Guide

Back to Resume

Assisted Living Director Resume Example & Writing Guide