Co-Op, Finance

Lila Sciences • Cambridge, MA

9d

About The Position

Lila Sciences Finance is embedding AI across Strategic Finance, FP&A, Procurement, and Accounting. The Co-Op will help move the team from informal experimentation to practical tools that are used in daily work. The role will identify high-impact AI use cases, build prototypes using LLM APIs and internal data, and measure the resulting time savings, accuracy gains, and adoption impact.

The Co-Op will work directly with finance stakeholders, learn the existing finance technology stack, and turn ambiguous workflow problems into shippable proof-of-concept tools. Successful pilots will be supported through rollout, and lessons and best practices will be documented for adoption across the broader Finance team. This is a hands-on position at the intersection of applied AI and corporate finance, and shipped work will be put into use immediately.

Requirements

• Hands-on experience using an LLM API, such as Anthropic, OpenAI, or similar, to build something beyond chat.
• Finance or business coursework sufficient to partner credibly with FP&A, Procurement, and Accounting stakeholders.
• Comfort ramping quickly on unfamiliar business software and integrating against it.
• Strong written communication.
• Ability to scope ambiguous problems into shippable prototypes.
• Currently pursuing an undergraduate or master's degree.
• Available for the full January to June term.

Nice To Haves

• Exposure to forecasting, variance analysis, or financial reporting workflows.
• Prior hands-on use of ERP, FP&A, expense, or procurement platforms.
• Experience working with internal datasets or data pipelines.
• Familiarity with evaluating and measuring AI tool impact.

Responsibilities

• Ramp quickly on the Finance team's existing technology stack across ERP, FP&A, expense, and procurement systems.
• Partner with FP&A, Procurement, Accounting, and Strategic Finance to identify high-value AI use cases.
• Prototype tools using LLM APIs against Finance workflows and internal data sources from existing systems.
• Measure time savings, accuracy gains, and adoption impact for each prototype.
• Scope ambiguous problems into shippable proof-of-concept tools.
• Document what works and capture best practices for broader Finance team adoption.
• Support the rollout of successful pilots from prototype to team-wide use.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Education Level: No Education Listed