Data Analyst

Overview

Partner with business stakeholders and other analysts to understand business data needs, capture data requirements, and perform data collection, processing and cleaning. Provide inputs for data science and business intelligence projects and perform analytical on large data sets to support departmental and organizational objectives. Growing an understanding of business needs and objectives. Solve a range of mostly straightforward problems with some increased scope and complexity. Developing professional with basic skill set and proficiency with procedures and analysis techniques.

Navy Federal Credit Union currently does not provide sponsorship for this role. Applicants must be authorized to work in the United States without the need for current or future sponsorship.

Responsibilities

• Contribute to the development of Data Transfer Authorizations including data definitions/classifications, business justifications, and source and destination details; conduct discovery, build data flow diagrams, lead meetings, and partner with Infosec to ensure successful completion.
• Assist with Data Governance efforts and quality data audits and analysis
• Identify and compile data sets using a variety of tools to help predict, improve, and measure the success of key business-to-business outcomes
• Document data collection, cleaning, and governance procedures, maintaining comprehensive documentation to ensure transparency, repeatability, and compliance with data governance standards
• Clean and organize raw data and generate descriptive statistics in support of business intelligence and data science projects
• Partner with senior staff to communicate findings and insight to stakeholders
• Collaborate with team members and participate in team projects and initiatives
• Provide data research and write data queries for smaller analytics projects

Qualifications

• 2-5 years of experience in data analysis and reporting
• Basic understanding of business and operating environment
• Strong understanding of advanced data cleaning and preprocessing techniques and tools
• Effective skill with analytical techniques required for data usage and data cleaning
• Skill interpreting, extrapolating and interpolating data for statistical research and modeling
• Knowledge of various data structures and ability to extract data sources (e.g., PySpark, PowerBI, SQL, SQL Server Integration Studios)
• Knowledge of data governance principles and practices
• Bachelor's Degree in Statistics, Mathematics, Computers Science, Engineering, or degrees in similar quantitative fields

Additional Information

Hours:

• Monday - Friday, 8:00AM - 4:30PM
  

Location:

• 820 Follin Lane, Vienna, VA 22180
• 5510 Heritage Oaks Drive, Pensacola, FL 32526
• 141 Security Drive, Winchester, VA 22602

About Us