Summer Associate Internship (Fraud Data Quality Analyst) in Vienna, VA at honor foundations

Date Posted: 12/3/2024

Job Snapshot

Job Description

Team Overview: The Data Engineering team, which is a part of Fraud Systems and Technology, is primarily focused on managing cloud data pipelines and governance. One of the team's key initiatives for FY 2024 involves decommissioning on-prem servers, including ATOM. The DE team collaborates with various enterprise functions and business units within NFCU to ensure that the data infrastructure effectively enables near-real-time fraud detection and prevention. Key stakeholders include Fraud Data & Reporting, Fraud Detection, Data Science & Machine Learning, Fraud Operations within Security, Enterprise Data and Information Management (EDIM), Enterprise Data Governance (EDG), and Enterprise Data and Analysis Services (EDAS – formerly MD).

Potential Projects:

  • Cloud data ingestion requests for Fraud teams 

  • Real time data architecture analysis

  • Cloud data quality concerns, as well as data quality analysis requests 

  • Databricks and SQL code performance reviews 

  • DTA process owner and consultant, for new and recertifications

    The Summer Associate Program is a 12-week internship program beginning in May 2025 and ending in August 2025. Students will work on impactful projects and meaningful work during their internship. To qualify for this position, applicants must be currently pursuing a degree from an accredited college or university and have an anticipated graduation date of December 2025 or later.

    About Us

    Navy Federal provides much more than a job. We provide a meaningful career experience, including a culture that is energized, engaged and committed; and fierce appreciation for our teams, who are rewarded with highly competitive pay and generous benefits and perks.

    Our approach to careers is simple yet powerful: Make our mission your passion.

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    From Fortune. ©2024 Fortune Media IP Limited. All rights reserved. Used under license. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of, Navy Federal Credit Union.

    Equal Employment Opportunity: Navy Federal values and celebrates diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected Veteran.

    Hybrid Workplace: Navy Federal Credit Union is a hybrid workplace, and details will be discussed during your interview process.

    Disclaimers: Navy Federal reserves the right to fill this role at a higher/lower grade level based on business need. An assessment may be required to compete for this position. Job postings are subject to close early or extend out longer than the anticipated closing date at the hiring team’s discretion based on qualified applicant volume. Navy Federal Credit Union assesses market data to establish salary ranges that enable us to remain competitive. You are paid within the salary range, based on your experience, location and market position.

    Bank Secrecy Act: Remains cognizant of and adheres to Navy Federal policies and procedures, and regulations pertaining to the Bank Secrecy Act.

    Qualifications
    • Currently pursuing a master’s degree in Statistics, Mathematics, Computers Science, Engineering, or degrees in similar quantitative fields.
    • Bachelor's Degree in Statistics, Mathematics, Computers Science, Engineering, or degrees in similar quantitative fields. 
    • 1-2 years of experience in data analysis and reporting
    • Familiarity with data cleaning and preprocessing techniques and tools
    • Knowledge of data cleaning and other analytical techniques required for data usage
    • 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)
    Responsibilities
    • Contribute to the development of technical requirements including data definitions, business rules, and data quality requirements; conduct data UAT, and data accuracy, validation, integrity research
    • Ensure compliance with deliverable reporting requirements by performing 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
    • Clean and organize raw data and generate descriptive statistics in support of business intelligence and data science projects
    • Support and participate in team projects and initiatives 
    • Research data quality concerns and contribute to data documents or project plans