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San Francisco, California, United States
Onsite
Factory is bringing autonomy to software engineering. We are actively looking for a Business Operations hire to drive the highest-priority initiatives that support Factory’s next phase of growth. This role sits at the intersection of strategy, finance, operations, marketing, growth, BD and go-to-market. You’ll report directly to bizops leadership and lead cross-functional projects that define how Factory scales. From building financial models to designing scalable processes and playbooks, you’ll be central to shaping our trajectory.
Design and implement scalable processes across GTM, customer success, finance and core operations.
Create compelling materials for strategic presentations and external partnerships.
Build and own financial models and business metrics to inform strategic decisions.
Develop customer success playbooks that drive adoption, activation, and measurable value.
Lead cross-functional projects across customer success, partnerships, community-building, and more.
Build dashboards and reporting systems to drive data-informed decisions across the business.
Partner closely with leadership and technical teams to ensure operational excellence as we scale.
3-4 years of experience at a top consulting firm, investment bank, private equity fund, or high-growth startup.
Exceptional analytical and problem-solving abilities, with strong data analysis and/or financial modeling skills.
Proven track record of thriving in ambiguous environments and driving results under pressure.
Outstanding written and verbal communication.
Ability to break down complex problems and execute structured solutions.
Experience with or excitement for using the latest AI tooling (including Factory!) to increase efficiency across all functions.
Experience collaborating closely with technical teams and products.
Nice to have
Experience in AI/ML or enterprise software companies.
Background in B2B SaaS operations.
Technical background or basic coding abilities.
Proven record of scaling operations at early-stage startups.
