À propos de ce poste Co-Op, Finance chez Lila Sciences
Your Impact at LILA
Lila Sciences Finance is building AI into how the function works, not as a side experiment but as an embedded capability across Strategic Finance, FP&A, Procurement, and Accounting. We need someone to help us go from informal experimentation to shipped tools the team actually uses.
This co-op will work across the Finance organization to identify high-impact AI use cases, prototype working tools against our internal data, and measure the time and accuracy gains those tools produce. You will partner directly with finance stakeholders, get up to speed on the team's existing finance tech stack, build proof-of-concept tools with LLM APIs, and help us turn successful pilots into a playbook the broader Finance team can scale.
This is a hands-on role at the intersection of applied AI and corporate finance. The work you ship will go into use immediately.
What You'll Be Building
- Ramp quickly on the Finance team's existing tech 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 of 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 You'll Need to Succeed
- Hands-on experience using an LLM API (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 July to December term
Bonus Points For
- 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
About LILA
Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.
LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.
Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.
We’re All In
Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.
A Note to Agencies
Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.