Your Impact at LILA

Lila is looking for a Fall Co-Op (Intern), Software Product Management to support software and workflow improvements across our scientific software platform.

This role sits at the intersection of scientists, software engineering, and product. The co-op will shadow users, help translate recurring workflow needs into clear product requirements, and support the team's work to connect designs, data, results, and learnings across scientific workflows.

The role is well suited for someone interested in product management, scientific operations, lab software, or data systems. The co-op will gain hands-on exposure to how scientific workflows become software requirements, while owning a small scoped feature or workflow improvement from discovery through delivery.

What You'll Be Building

• Shadow scientists and other users to understand their software and workflow needs.
• Help groom product backlogs with product, science, and engineering partners.
• Write clear user stories and acceptance criteria from ambiguous requirements.
• Support connecting designs, data, and results across scientific workflows.
• Triage recurring user asks and convert them into actionable tickets.
• Own a small scoped feature or workflow improvement from discovery through delivery.
• Partner with engineers and scientists to clarify requirements, acceptance criteria, and workflow impact.

What You'll Need to Succeed

• Interest in product management, scientific workflows, lab operations, or software systems.
• Strong written communication skills and ability to turn ambiguity into clear requirements.
• Comfort working with cross-functional partners across science, product, and engineering.
• Ability to observe workflows, ask thoughtful questions, and synthesize user needs.
• Organized approach to tracking tasks, decisions, and follow-ups.
• Curiosity about how software can improve experimental throughput, traceability, and data quality.

Bonus Points For

• Experience with product backlogs, user stories, or acceptance criteria.
• Exposure to scientific data systems, lab software, or workflow tools.
• Prior internship, coursework, or project work involving product, operations, or software delivery.