VyStar Intern-Advance Analytics

VyStar Credit Union•Jacksonville, FL

9h•Onsite

About The Position

At VyStar, we offer competitive pay, an excellent benefit package that includes a 401(k) Plan, an extensive paid technical and on-the-job training program, and tuition reimbursement--available to all full and part time employees. Part time positions start at a minimum of 30 hours per week. We encourage you to become a part of VyStar Credit Union's family of employees. VyStar Intern-Advance Analytics Life as a VyStar Intern: At VyStar Credit Union we are passionate about our members and our employees. For more than 70 years, VyStar has adapted to changes in the banking industry. Today, we have grown to be one of the largest Credit Unions in the United States serving more than 1 million members. Our mission ‘Do Good Bank Better’ drives our employees every day to raise the bar on how we serve our members, our community, and each other. VyStar is proudly seeking talented interns to be involved in a broad range of projects, while gaining a strong foundation of the Credit Union business. This is an exciting time to join VyStar! VyStar’s paid internship experience is dynamic and tailored to your interests and needs of the organization. The internship is primarily located in the Jacksonville, FL headquarters office. The 9-week internship program begins first week of June and concludes the first week of August. What you’ll do: This position will partner with several members of the Advanced Analytics Group (AAG) on key projects during their internship. By the end of the internship, the intern will have completed a business deliverable that can be showcased as part of a professional skillset portfolio. They will strengthen both technical and business competencies through hands-on experience and gain a deeper understanding of how to operate effectively within a business enterprise. Projects may include: AAG  Modeling MLOps – Develop machine‑learning operations skills by building, deploying, and maintaining production ML pipelines. Work with compute, orchestration, and CI/CD tools to automate testing, linting, and deployment. Design reproducible data‑ and feature‑engineering workflows using Databricks and implement monitoring, drift detection, and alerting dashboards to ensure model health and regulatory compliance.  These ML engineering abilities are highly sought after by employers and add tangible analytics deliverables to your résumé. AAG Modeling LLM Automation – Development and operationalizing Large Language Models (LLMs) through automated, end‑to‑end pipelines. Interns will work on data ingestion, prompt engineering, fine‑tuning, and deployment of LLMs, leveraging automation tools to create repeatable workflows. The goal is to deliver a production‑ready LLM solution—complete with monitoring, drift detection, and documentation—that can be showcased as a concrete analytics achievement. These AI engineering abilities are highly sought after by employers and add tangible analytics deliverables to your résumé. AAG Modelling Data Science – Develop data‑science and machine‑learning skills by wrangling real‑world data and creating predictive and prescriptive models that solve concrete business problems. The modelling use case will be scoped for on‑the‑job training, allowing you to apply learnings to a live model‑development project for a business partner. These data‑science and data‑wrangling abilities are highly sought after by employers and add tangible analytics deliverables to your résumé. Scrum Master and/or Product Owner – Gain experience in product ownership and agile workflows, including sprint planning, backlog management, stakeholder communication, and iterative delivery. You will practice leading ceremonies, tracking progress, and ensuring that development teams stay aligned with business priorities. All employees and business units, as first line of defense, are expected to proactively help identify, assess, manage, and report risks within their domain of work. To enhance a healthy risk culture and support our growth for good pillar, employees will maintain vigilance in safeguarding our operations while ensuring compliance with regulatory mandates. The Risk team serves as the second line of defense by providing risk oversight and credible challenge whereas the Audit team serves as the third line of defense by providing risk assurance. As an intern, you will: Get hands-on experience solving business needs Expand your team player capabilities Develop your leadership and business acumen Interact with Senior Executives Get paired with a mentor Expand your business network Join in community events And more…

Requirements

Pursuing a Bachelor’s degree at an accredited college/university
Rising College Juniors, Seniors, Graduate Students, or Thrive Scholars
Strong written and communication skills
Participation in college organizations and the community
Flexibility to work with multi-disciplined teams
Strong use of Microsoft Office Tools

Nice To Haves

GPA of 3.0 preferred
Educational Majors preferred, but not limited to: Data Analytics, Data Governance, Data Engineering, Systems Analysts, Business, Business Analytics, Data Policy/Insight/Integrity, Data Science, Data Management, Mathematics with Computer Science Minor
Preferred, but not necessary, certifications in Lean/Six Sigma; Agile/Scrum; Coding & Analytics Programs such as Python, R, and related packaged applications such as Power BI, and Data Bricks

Responsibilities

Partner with several members of the Advanced Analytics Group (AAG) on key projects during their internship.
Complete a business deliverable that can be showcased as part of a professional skillset portfolio.
Strengthen both technical and business competencies through hands-on experience
Gain a deeper understanding of how to operate effectively within a business enterprise.
Develop machine‑learning operations skills by building, deploying, and maintaining production ML pipelines.
Work with compute, orchestration, and CI/CD tools to automate testing, linting, and deployment.
Design reproducible data‑ and feature‑engineering workflows using Databricks and implement monitoring, drift detection, and alerting dashboards to ensure model health and regulatory compliance.
Work on data ingestion, prompt engineering, fine‑tuning, and deployment of LLMs, leveraging automation tools to create repeatable workflows.
Deliver a production‑ready LLM solution—complete with monitoring, drift detection, and documentation—that can be showcased as a concrete analytics achievement.
Develop data‑science and machine‑learning skills by wrangling real‑world data and creating predictive and prescriptive models that solve concrete business problems.
Gain experience in product ownership and agile workflows, including sprint planning, backlog management, stakeholder communication, and iterative delivery.
Practice leading ceremonies, tracking progress, and ensuring that development teams stay aligned with business priorities.
Proactively help identify, assess, manage, and report risks within their domain of work.
Maintain vigilance in safeguarding our operations while ensuring compliance with regulatory mandates.