Job Description

Team Overview:

Operational Technologies (OT) is a team within the Service Transition branch of NFCU’s Information Services Department (ISD). The team's primary responsibility is working with IT, industrial internet of things (IoT) and operational technology teams to lead technology driven business process transformation and innovation for Navy Federal Credit Union. We partner with IT, Risk, Security and Audit teams to establish operational compliance that streamlines operations while protecting the organization.  Team members possess Industry and Technology acumen, are familiar with business systems (IT), plant operations environment (OT), Cyber Security, Network Security, and the ability to connect these domains to form the enterprise solutions approach. 

Potential Project:

OT data analyst/scientist must understand the differences in the processing and management of data on the edge, where OT happens, versus traditional infrastructure. 

12-week plan:

• Provide a developmental plan of predictive analytics for OT devices through data ingested by the OT software.  The analytics should provide a way of identifying potential problems with the environment or equipment minimizing issues 
• Create customized reporting from data collected from the OT software tool and provide a way to automate/schedule reporting
• Collaborate with ServiceNow to ensure data ingestion is migrating into ServiceNow accurately.      Resolve all discrepancies
• Represent OT Management on various enterprise governance boards, as needed for assuring requirements are addressed in updates to existing enterprise environment, policies/standards, and projects

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.

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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• Ripplematch Campus Forward Award - Excellence in Early Career Hiring
• Yello and WayUp Top 100 Internship Programs

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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.

• Experience:  Total Professional Experience 5+ years of which Information Technology Experience is 3+ years and at least 1 year OT/IoT Experience
• Currently pursuing a graduate degree in Computer Science, Management Information Systems, Artificial Intelligence, Computer Engineering, or Software Engineering

Business Soft Skills:

• Excellent communication skills
• Self-starter / self-directed
• Understanding of general Information Technology concepts
• Experience with business process definition and optimization
• Strong analytical skills with experience creating reports and analyses
• High level proficiency with Microsoft Office

Technical Skills Preferred (as many of the following):

• Experienced in the Fundamentals of Data Science
• Experience with Statistical Analysis
• Experience with Machine Learning and Big Data
• Experience with Data Visualization
• Experience programming with both scripting languages and 3GLs, such as C / C++, Java, C#, Python, etc.…
• Experience with Data Manipulation and Analysis
• Experience with process management and process automation tools
• Experience with SQL, Reporting and Analytic tools
• Experience with Infrastructure Management and Operations Management
• Understanding of ITIL and other control frameworks
• Understanding of and experience with ServiceNow – ITBM / SM / CM / PM / IM / CMDB / RM
• Understanding of Waterfall / Agile / DevOps / Site Reliability Engineering (SRE) approach to software development
• Understanding of Software Development Lifecycle (SDLC) approaches

• The skills an OT data analyst/scientist must have:  All data analyst/scientists should be well-versed in machine learning and deep learning, but OT data analyst/scientists also require different skills from traditional data scientists.
• Identifies relevant data sets needed for data analytic applications
• Works with others to collect, integrate and prepare data for analysis
• Develops and runs analytical models and assess the findings
• Communicates the results to business owners, users and others as needed
• Preprocessing of data:  Data doesn't flow out of OT in tidy, well-formatted records, as it does in conventional systems. OT data is often sparse or incomplete, subject to the whims of the environment and the state of the machine producing it and it varies under changing conditions. The data is frequently temporal and time sensitive. OT data analyst/scientists can apply deep learning to spot conditional shifts in data patterns, make predictive assessments of data quality and fill in the gaps as needed.