About this role
The SWE Ops Infrastructure & Planning team is committed to fostering a culture of technical excellence and operational discipline. As our research and engineering initiatives grow in scale and complexity, we are looking for an analyst who thrives in bringing structure to ambiguity, connecting the bigger picture to operational execution, and bringing decision-ready insights to various levels of leadership.
The ideal candidate pairs strong project management acumen and deep analytical capability with exceptional interpersonal skills. You will drive alignment across machine learning scientists, engineering DRIs, finance, and cross-functional partners—championing clarity, accountability, and continuous improvement while ensuring disciplined stewardship of our resources through proactive forecasting and vendor management. You embody a passion to fight for excellence (striving for exceptional outcomes without settling) and the foresight to see around corners (anticipating long-term organizational, technological, and strategic trajectories). 5+ years of business operations, financial planning & analysis, strategy & operations experience within a high-tech or software engineering environment.
Bachelor’s degree in an analytical or quantitative discipline (such as Business, Finance, Operations, Supply Chain), or equivalent practical experience.
Proven track record managing the end-to-end Purchase Requisition (PR) to Purchase Order (PO) lifecycle—including vendor onboarding, scoping alignment, and proactive cross-functional chasing.
Solid grasp of core financial treatment principles: CapEx vs. OpEx, prepaid assets, accruals, amortization schedules, and milestone-based billing.
Demonstrated ability to track, analyze, and reconcile budget actuals vs. forecasts, identifying variances and driving corrective actions before quarter-end.
Exceptional executive communication skills: ability to distill complex procurement timelines and financial figures into crisp, high-level narratives and executive summaries.
Superior written and verbal communication skills, with proven ability to distill complex technical/operational information into clear, executive-ready presentations and memos. CPA or MBA
Experience working with data licensing, or technical vendor contracts.
Direct experience partnering with or supporting Machine Learning, AI, or R&D research teams.
Familiarity with data analysis, querying, and visualization tools (e.g., SQL, Excel, Tableau) to evaluate organizational metrics and build automated reporting.
A natural curiosity for AI/ML technologies and how strategic investments fuel model development.
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