NeoGenomics has an opening for an AI Finance Innovation Intern who wants to continue to learn in order to allow our company to grow. This position is onsite in Fort Myers or SoCal (Aliso Viejo or Carlsbad) offices.
Now that you know what we're looking for in talent, let us tell you why you'd want to work at NeoGenomics:
As an employer, we promise to provide you with a purpose driven mission in which you have the opportunity to save lives by improving patient care through the exceptional work you perform. Together, we will become the world's leading cancer reference laboratory.
Position Summary:
NeoGenomics has made the decision to bring AI into its Finance operations. This role exists to help execute the vision. NeoGenomics has identified a set of priority use cases where AI can meaningfully improve how our Finance function operates reducing manual work, improving analytical quality, and freeing capacity for higher-value decision support. We are looking for an intern to implement them.
You will arrive with a defined scope and a real objective: build AI-enabled solutions against identified opportunities, integrate them into active Finance workflows, and ensure the team is equipped to use and sustain them after you leave. This requires technical capability, financial literacy, and the interpersonal judgment to drive adoption in a team that did not design the solution.
You will work within an established compliance framework, with guidance from finance leadership on the auditability, data integrity, and internal control standards that apply to each solution. Governance is built into how we work and you will be supported in understanding what that means in practice.
Core Responsibilities:
ONBOARDING AND CONTEXT
-
Develop a working understanding of the Finance workflows associated with each assigned use case, including data sources, process steps, decision points, and current pain points, through direct observation and structured conversations with the team.
-
Review the use case briefs prepared by finance leadership, ask clarifying questions, and align with your manager on scope, success criteria, and delivery milestones before moving into build.
SOLUTION BUILD AND INTEGRATION
-
Design and build AI-enabled solutions for each assigned use case, applying appropriate tools and techniques to the specific workflow being improved.
-
Ensure each solution is integrated into the team’s active workflow not delivered as a standalone artifact with clear handoffs to the analysts and business partners who will use it day to day.
-
Build with auditability and internal controls in mind from the start; solutions must maintain data integrity, produce reproducible outputs, and meet any SOX compliance requirements applicable to the relevant process.
-
Conduct structured testing against real Finance data and scenarios, identify failure modes, and iterate until the solution performs reliably under conditions the team will actually encounter.
DOCUMENTATION
-
Produce clear, complete documentation for each implemented solution, written for who will maintain the solution covering inputs, logic, outputs, known limitations, and step-by-step operating instructions.
-
Maintain a solution log throughout the internship that captures design decisions, iterations, and lessons learned creating an institutional record that survives beyond the internship itself.
ADOPTION AND ENABLEMENT
-
Partner with the analysts and business partners who will own each solution after your internship ends, ensuring they understand how it works, when to use it, and how to identify when something has gone wrong.
-
Conduct working sessions or training as needed to build comfort and confidence with each solution among the relevant users, addressing questions and concerns directly rather than through written documentation alone.
-
Gather end-user feedback throughout implementation and use it to improve solutions before the internship ends.
-
Present a final summary to finance leadership at the conclusion of the internship, covering what was built, what was adopted, and any recommendations for continued development.
Experience, Education and Qualifications:
Required:
-
Currently enrolled in an undergraduate or graduate program in Finance, Accounting, Information Systems, Business Analytics, or a related field
-
Demonstrated experience building with AI tools in an applied context coursework, independent projects, or prior work experience all count
-
Ability to work within a defined scope and deliver against milestones in a structured, time-bound environment
-
Proficiency in Excel and comfort working with financial and quantitative data
-
Strong communication and interpersonal skills; able to explain how a solution works to someone who did not build it and to earn adoption from business partners who are accustomed to doing things differently
-
High attention to detail and a personal standard for output quality consistent with a regulated, audit-facing environment
Preferred:
-
Prior internship or work experience in a finance, accounting, or analytical role
-
Familiarity with internal controls, SOX compliance, or financial data governance in a corporate environment
-
Experience building solutions that other people use in any context, technical or otherwise
-
Proficiency in SQL, Python, Tableau or comparable analytical tools
-
Prior experience writing technical documentation for a non-technical audience
What You Will Gain:
-
Demonstrated history of delivering results you will contribute implemented solutions actively utilized by a publicly traded company, rather than providing only presentation materials or prototypes.
-
Deep, practical experience with AI implementation inside the governance constraints that enterprise environments impose, including auditability, data integrity, and compliance requirements most early-career professionals never encounter.
-
Hands-on experience driving adoption the organizational skill of making something new stick which is consistently harder than building the solution itself and consistently more valuable on a resume.
-
Executive visibility: your final presentation will be delivered to finance leadership, and your work will be evaluated on whether it is still in use after you leave, not on how it looked in a demo.
-
A substantive portfolio of documented, real-world AI implementations with concrete business context to speak to in future interviews
