Overview As an Associate Project Manager, you enable efficient delivery of eDiscovery projects within the DISCO platform, collaborating with cross-functional teams to support client success. You balance low-to-moderate complexity work, provide product guidance to clients, and help ensure quality and timely execution. You act as a DISCO advocate, delivering training and maintaining clear client communication. This role offers exposure to AI-enabled workflows and opportunities to shape best practices in legal technology.
Pay / Benefits - medical and dental insurance
- discretionary bonus
- RSUs
- competitive salary
- startup growth opportunities
- inclusive environment
Responsibilities - Collaborate with Project Managers and cross-functional teams to deliver high-quality client service
- Own execution of core, low-to-moderate complexity matters and discrete billable tasks
- Ensure efficient service delivery and platform usage to minimize user errors
- Maintain project tracking to meet deadlines
- Develop advanced knowledge of the DISCO platform to advise clients on best practices
- Provide feedback and feature requests to product/engineering teams
- Build rapport with clients and communicate status and product functionality
- Deliver product training to attorneys, paralegals, and litigation support specialists
Key requirements - 1+ years of eDiscovery project management experience (or equivalent education)
- 1+ years working with industry-standard eDiscovery platforms (DISCO, Relativity, Everlaw, Reveal, Recommind)
- 1+ years experience at a consulting firm or providing consultative solutions in eDiscovery
- 1+ years experience in a litigation support group at law firm/corporation
- 1+ years experience with data collection and processing software
- Clear, professional written and verbal communication
- Strong organizational habits and task management
- Proactive problem-solving
- eDiscovery platforms (DISCO, Relativity, Everlaw, Reveal, Recommind)
- data collection and processing software
- platform navigation and best practices for early data assessment, document review, and production
