Spring 2027 Finance Systems Co-op

Groma•Boston, MA

10d•Onsite

About The Position

The Finance Systems Co-op will help Groma’s Finance team use AI to work more efficiently and accurately. Over six months, the co-op will learn finance and accounting processes, identify opportunities for improvement, and design and implement solutions using tools such as Claude, ChatGPT, Python, SQL, and financial platforms. The role is intended for someone who can serve as an in-house AI expert and help colleagues build their fluency with these tools. Groma is a real estate and technology company developing property and investor technology platforms for small-unit multifamily real estate. The company describes its culture as fast-growing, ambitious, collaborative, and focused on thoughtful solutions to real-world challenges. The role is based at Groma’s headquarters in downtown Boston, with an in-office culture; occasional work from home or on the road is recognized as necessary. This is a six-month, 40-hour-per-week co-op paid at $20 per hour.

Requirements

Pursuing a degree in Computer Science, Data Science, AI, Systems Engineering, Management Information Systems, Business Analytics, Fintech, or Finance with a focus on technical coursework.
Working knowledge of Python, SQL, and REST APIs.
Strong spreadsheet skills, including Google Suite.
Ability to recognize when AI output needs checking and when it can be trusted.
Ability to explain technical work clearly to people who do not code.
Diligent documentation and task management.
Excellent communication skills.
Ability to work independently and as part of a team.

Nice To Haves

Finance exposure.
An example of something built with LLM tools to share in the application.

Responsibilities

Automate recurring finance tasks with AI workflows, including Claude, ChatGPT, and their APIs.
Map finance processes and prioritize opportunities for automation.
Connect financial platforms, databases, APIs, and other systems to create more efficient workflows.
Build automations with human review steps and audit trails.
Serve as the team’s in-house AI expert and increase colleagues’ AI fluency.
Document systems so non-technical teammates can operate them.
Support accounts payable and accounts receivable to learn finance processes firsthand.
Analyze financial data for trends and exceptions, and support reporting and auditing.
Take on special projects where a technical approach is more effective than a manual one.