J-1 Visa Data Engineer Intern Jobs
Data Engineer Intern roles in the U.S. are accessible through J-1 visa sponsorship under the Intern category, which is designed for degree-seeking students gaining hands-on experience in their field of study. A designated sponsor organization issues your DS-2019 and your host employer provides the actual internship placement.
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We are seeking a highly motivated and detail-oriented Data Scientist Summer Associate to join the Member Insights & Experience Analytics team within Lending Strategy. This internship is designed for graduate-level students who are passionate about data science, machine learning, analytics, and improving customer experiences through data.
The Member Insights & Experience Analytics team serves as the voice of the member by leveraging advanced analytics to better understand member behaviors, preferences, and experiences across the lending lifecycle. The team combines member data, digital interactions, and voice-of-the-member feedback to deliver actionable recommendations that improve member engagement, satisfaction, and business outcomes. This work supports Lending leadership, product teams, operational partners, and member experience stakeholders.
As a Summer Associate, you will work alongside data scientists and analytics professionals to develop models, uncover insights, and translate member interaction data into meaningful business recommendations. A primary focus of the internship will be leveraging advanced analytics and AI techniques to analyze lending-related member calls, identify emerging themes, measure sentiment, and uncover opportunities to improve the member experience.
The Summer Associate Program is a 12-week internship program beginning in May 2027 and ending in August 2027. 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 2027 or later.
Responsibilities
Current Data Science Projects
- Lending Call Sentiment Analytics
Objective: Measure and monitor member sentiment across lending-related interactions to identify opportunities to improve the borrower experience.
Description: Develop sentiment models using call transcripts and interaction data to identify positive, neutral, and negative member experiences. Analyze sentiment trends across lending products, servicing processes, and member journeys to uncover pain points, operational challenges, and opportunities to improve satisfaction and engagement. Findings will support Voice of the Member initiatives and experience improvement efforts.
- Lending Call Topic Modeling
Objective: Identify and track key themes, concerns, and emerging issues within member lending conversations.
Description: Apply Natural Language Processing (NLP) techniques to call transcripts and interaction data to automatically classify and cluster member conversations. The model will surface common topics such as application issues, underwriting questions, servicing inquiries, payment concerns, digital experience challenges, and member friction points. Insights will help business leaders prioritize improvements and address emerging member needs.
- Voice of the Member Insights Dashboard
Objective: Deliver self-service analytics that provide visibility into member experience trends and emerging issues.
Description: Build interactive dashboards that combine sentiment scores, topic trends, call volumes, operational metrics, and member outcome data. These dashboards will help stakeholders monitor member experience KPIs, identify areas requiring attention, and evaluate the impact of process improvements.
- Collaborate with Lending Strategy, Member Experience, Product, and Operational partners to understand business challenges and translate them into analytical solutions.
- Perform data preparation, feature engineering, exploratory data analysis (EDA), and model development using structured and unstructured data sources.
- Develop Natural Language Processing (NLP) models to analyze lending-related call transcripts and member feedback.
- Build sentiment analysis and topic modeling solutions to identify member concerns, emerging trends, and experience improvement opportunities.
- Create dashboards and visualizations using Power BI to communicate findings to business stakeholders.
- Write efficient and scalable code in Python and SQL to manipulate and analyze large datasets.
- Apply statistical modeling, machine learning, and AI techniques to solve business problems and uncover actionable insights.
- Present findings and recommendations to technical and non-technical audiences.
- Document methodologies, model assumptions, and analytical processes to support governance and knowledge sharing.
- Support the development of data products and AI-enabled analytics capabilities within Lending Strategy.
- Perform other related duties as assigned.
BASIC QUALIFICATIONS
- Must be currently enrolled in, or planning to enroll in, a graduate-level program (Master’s) in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a closely related field following completion of undergraduate studies.
- Proficiency in Python and SQL.
- Familiarity with machine learning and Natural Language Processing (NLP) techniques.
- Experience with data cleaning and exploratory data analysis (EDA).
- Familiarity with data visualization tools such as Power BI and Dash.
- Strong analytical and problem-solving skills.
- Excellent communication and collaboration abilities.
PREFERRED QUALIFICATIONS
- Demonstrate intellectual curiosity by asking thoughtful questions, challenging assumptions, and independently identifying opportunities for deeper analysis that improve understanding of member behavior and experience.
- Experience with R programming.
- Background in statistics, mathematics, or machine learning.
- Exposure to big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., Azure, AWS, GCP).
- Understanding of version control systems like Git.
WHAT YOU’LL GAIN
- Hands-on experience solving real business problems using data science.
- Mentorship from experienced professionals in analytics and business intelligence.
- Exposure to enterprise-level tools and technologies.
- Opportunity to present your work to senior leadership.
- A collaborative and inclusive work environment.
ADDITIONAL INFORMATION
Hours:
- Monday – Friday, 8:00AM - 4:30 PM ET
Location:
- 820 Follin Lane, Vienna, VA 22180
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.
- FORTUNE100 Best Companies to Work For® 2025
- Yello and WayUp Top 100 Internship Programs
- Computerworld® Best Places to Work in IT
- Newsweek Most Loved Workplaces
- 2025 PEOPLE® Companies That Care
- Newsweek Most Trustworthy Companies in America
- Military Times 2025 Best for Vets Employers
- Best Companies for Latinos to Work for 2025
- Forbes® 2025 America’s Best Large Employers
- Forbes® 2025 America's Best Employers for New Grads
- Forbes® 2025 America's Best Employers for Tech Workers
- 2025 RippleMatch Campus Forward Award Winner for Overall Excellence
- Military.com Top Military Spouse Employers 2025
- 2025 Handshake Early Talent Award
From Fortune. ©2025 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: All qualified applicants will receive consideration for employment without regard to age, race, sex, color, religion, national origin, disability, veteran status, pregnancy, sexual orientation, genetic information, gender identity or any other basis protected by applicable law.
Accommodations: If you need accommodation or assistance for a qualifying condition to complete the online application (or during any stage of the hiring process), you can contact Navy Federal's Medical Accommodations team at medicalaccommodations@navyfederal.org or by calling 1-888-503-6013. This team cannot provide any information on job postings or application status.
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. For additional details regarding compensation and benefits, review the Benefits page of the Navy Federal Career Site.
Protect Yourself from Job Scams: Navy Federal Credit Union jobs are posted on our career site, jobs.navyfederal.org and reputable job boards (e.g., LinkedIn, Indeed). We do not post jobs on social media marketplaces, messaging apps or unverified websites. We will never ask candidates for payment, bank details or personal financial information during the hiring process.
Bank Secrecy Act: Remains cognizant of and adheres to Navy Federal policies and procedures, and regulations pertaining to the Bank Secrecy Act.
INTRODUCTION
We are seeking a highly motivated and detail-oriented Data Scientist Summer Associate to join the Member Insights & Experience Analytics team within Lending Strategy. This internship is designed for graduate-level students who are passionate about data science, machine learning, analytics, and improving customer experiences through data.
The Member Insights & Experience Analytics team serves as the voice of the member by leveraging advanced analytics to better understand member behaviors, preferences, and experiences across the lending lifecycle. The team combines member data, digital interactions, and voice-of-the-member feedback to deliver actionable recommendations that improve member engagement, satisfaction, and business outcomes. This work supports Lending leadership, product teams, operational partners, and member experience stakeholders.
As a Summer Associate, you will work alongside data scientists and analytics professionals to develop models, uncover insights, and translate member interaction data into meaningful business recommendations. A primary focus of the internship will be leveraging advanced analytics and AI techniques to analyze lending-related member calls, identify emerging themes, measure sentiment, and uncover opportunities to improve the member experience.
The Summer Associate Program is a 12-week internship program beginning in May 2027 and ending in August 2027. 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 2027 or later.
Responsibilities
Current Data Science Projects
- Lending Call Sentiment Analytics
Objective: Measure and monitor member sentiment across lending-related interactions to identify opportunities to improve the borrower experience.
Description: Develop sentiment models using call transcripts and interaction data to identify positive, neutral, and negative member experiences. Analyze sentiment trends across lending products, servicing processes, and member journeys to uncover pain points, operational challenges, and opportunities to improve satisfaction and engagement. Findings will support Voice of the Member initiatives and experience improvement efforts.
- Lending Call Topic Modeling
Objective: Identify and track key themes, concerns, and emerging issues within member lending conversations.
Description: Apply Natural Language Processing (NLP) techniques to call transcripts and interaction data to automatically classify and cluster member conversations. The model will surface common topics such as application issues, underwriting questions, servicing inquiries, payment concerns, digital experience challenges, and member friction points. Insights will help business leaders prioritize improvements and address emerging member needs.
- Voice of the Member Insights Dashboard
Objective: Deliver self-service analytics that provide visibility into member experience trends and emerging issues.
Description: Build interactive dashboards that combine sentiment scores, topic trends, call volumes, operational metrics, and member outcome data. These dashboards will help stakeholders monitor member experience KPIs, identify areas requiring attention, and evaluate the impact of process improvements.
- Collaborate with Lending Strategy, Member Experience, Product, and Operational partners to understand business challenges and translate them into analytical solutions.
- Perform data preparation, feature engineering, exploratory data analysis (EDA), and model development using structured and unstructured data sources.
- Develop Natural Language Processing (NLP) models to analyze lending-related call transcripts and member feedback.
- Build sentiment analysis and topic modeling solutions to identify member concerns, emerging trends, and experience improvement opportunities.
- Create dashboards and visualizations using Power BI to communicate findings to business stakeholders.
- Write efficient and scalable code in Python and SQL to manipulate and analyze large datasets.
- Apply statistical modeling, machine learning, and AI techniques to solve business problems and uncover actionable insights.
- Present findings and recommendations to technical and non-technical audiences.
- Document methodologies, model assumptions, and analytical processes to support governance and knowledge sharing.
- Support the development of data products and AI-enabled analytics capabilities within Lending Strategy.
- Perform other related duties as assigned.
BASIC QUALIFICATIONS
- Must be currently enrolled in, or planning to enroll in, a graduate-level program (Master’s) in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a closely related field following completion of undergraduate studies.
- Proficiency in Python and SQL.
- Familiarity with machine learning and Natural Language Processing (NLP) techniques.
- Experience with data cleaning and exploratory data analysis (EDA).
- Familiarity with data visualization tools such as Power BI and Dash.
- Strong analytical and problem-solving skills.
- Excellent communication and collaboration abilities.
PREFERRED QUALIFICATIONS
- Demonstrate intellectual curiosity by asking thoughtful questions, challenging assumptions, and independently identifying opportunities for deeper analysis that improve understanding of member behavior and experience.
- Experience with R programming.
- Background in statistics, mathematics, or machine learning.
- Exposure to big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., Azure, AWS, GCP).
- Understanding of version control systems like Git.
WHAT YOU’LL GAIN
- Hands-on experience solving real business problems using data science.
- Mentorship from experienced professionals in analytics and business intelligence.
- Exposure to enterprise-level tools and technologies.
- Opportunity to present your work to senior leadership.
- A collaborative and inclusive work environment.
ADDITIONAL INFORMATION
Hours:
- Monday – Friday, 8:00AM - 4:30 PM ET
Location:
- 820 Follin Lane, Vienna, VA 22180
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.
- FORTUNE100 Best Companies to Work For® 2025
- Yello and WayUp Top 100 Internship Programs
- Computerworld® Best Places to Work in IT
- Newsweek Most Loved Workplaces
- 2025 PEOPLE® Companies That Care
- Newsweek Most Trustworthy Companies in America
- Military Times 2025 Best for Vets Employers
- Best Companies for Latinos to Work for 2025
- Forbes® 2025 America’s Best Large Employers
- Forbes® 2025 America's Best Employers for New Grads
- Forbes® 2025 America's Best Employers for Tech Workers
- 2025 RippleMatch Campus Forward Award Winner for Overall Excellence
- Military.com Top Military Spouse Employers 2025
- 2025 Handshake Early Talent Award
From Fortune. ©2025 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: All qualified applicants will receive consideration for employment without regard to age, race, sex, color, religion, national origin, disability, veteran status, pregnancy, sexual orientation, genetic information, gender identity or any other basis protected by applicable law.
Accommodations: If you need accommodation or assistance for a qualifying condition to complete the online application (or during any stage of the hiring process), you can contact Navy Federal's Medical Accommodations team at medicalaccommodations@navyfederal.org or by calling 1-888-503-6013. This team cannot provide any information on job postings or application status.
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. For additional details regarding compensation and benefits, review the Benefits page of the Navy Federal Career Site.
Protect Yourself from Job Scams: Navy Federal Credit Union jobs are posted on our career site, jobs.navyfederal.org and reputable job boards (e.g., LinkedIn, Indeed). We do not post jobs on social media marketplaces, messaging apps or unverified websites. We will never ask candidates for payment, bank details or personal financial information during the hiring process.
Bank Secrecy Act: Remains cognizant of and adheres to Navy Federal policies and procedures, and regulations pertaining to the Bank Secrecy Act.
See all J-1 Visa Data Engineer Intern Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new J-1 Visa Data Engineer Intern Jobs.
Get Access To All JobsTips for Finding J-1 Visa Sponsorship as a Data Engineer Intern
Align your academic enrollment with Intern eligibility
The J-1 visa Intern category requires you to be currently enrolled in a degree program or have graduated within the past 12 months. Confirm your enrollment status with your DSO before applying, as hosts frequently verify this with the designated sponsor.
Build a training plan before approaching host employers
Designated sponsors require a formal Training or Internship Placement Plan before issuing your DS-2019. Draft a clear document mapping your data engineering tasks, tools like SQL and Spark, and specific learning objectives tied to your academic program.
Target host employers with existing data infrastructure teams
Focus on organizations that already run structured data pipelines or cloud platforms, since these roles map cleanly to the Intern category's field-of-study requirement. Research engineering team size and tech stack in job postings to assess fit before applying.
Search Migrate Mate to find J-1-aligned data internships
Use Migrate Mate to filter for Data Engineer Intern roles at U.S. employers that work with J-1 exchange visitors. The platform surfaces host employers open to sponsorship arrangements, saving you from cold outreach to companies unfamiliar with the DS-2019 process.
Verify whether your role triggers the two-year home residency requirement
Some J-1 participants must return home for two years before changing to certain other visa categories. Check your DS-2019 and USCIS guidance to determine if your country, funding source, or skill classification subjects you to this requirement before accepting any offer.
Confirm your host employer will cooperate with sponsor compliance reporting
Your designated sponsor, whether IIE, Cultural Vistas, or another SEVIS-registered organization, will require periodic check-ins and documentation from your host employer. Raise this expectation during offer negotiations so the employer is prepared before your DS-2019 is issued.
Data Engineer Intern J-1 Visa: Frequently Asked Questions
Which J-1 program category covers Data Engineer Intern positions?
The J-1 Intern category is the correct classification for most data engineering internships. It applies to individuals currently enrolled in a degree program outside the U.S., or who graduated within the past 12 months. The role must relate directly to your field of study, so a computer science, information systems, or engineering enrollment is typically required to qualify.
Who actually sponsors the J-1 visa for a data internship - the employer or a separate organization?
The visa sponsor is a U.S. Department of State-designated organization, not your employer. Organizations like IIE, Cultural Vistas, or CIEE issue the DS-2019 form and hold legal responsibility for program compliance. Your host employer provides the internship itself and cooperates with the sponsor's reporting requirements, but the employer is not the visa sponsor under J-1 rules.
How do I find U.S. employers open to hosting a J-1 data engineering intern?
Migrate Mate is built specifically for this search. It lets you filter for Data Engineer Intern roles at U.S. employers that are familiar with J-1 exchange visitor arrangements. This is more efficient than cold-applying to companies that may not understand the DS-2019 process or the host employer obligations required by a designated sponsor.
Does a data engineering internship under J-1 require a formal training plan, and what should it include?
Yes. Your designated sponsor requires a completed Training or Internship Placement Plan before issuing the DS-2019. For a data engineering role, the plan should document specific technical tasks, tools you'll use such as Python, SQL, or cloud platforms, measurable learning objectives, and how the work connects to your academic program. Vague descriptions are frequently rejected.
Can I stay in the U.S. after my J-1 data internship ends, or must I leave immediately?
J-1 Intern participants receive a 30-day grace period after their program end date to prepare for departure. You cannot work during this period. If you're subject to the two-year home residency requirement, you'll need to return home before applying for most employment-based visa categories. Check your DS-2019 and USCIS guidance to determine whether this requirement applies to your situation.