Lead Financial Analyst
New
United StatesFull-TimeLead
Salary108,000 - 135,000 USD per year
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Job Details
- Experience
- 6+ years
- Required Skills
- Data AnalysisMicrosoft ExcelStakeholder managementSaaS
Requirements
- 6+ years of experience in financial planning and analysis, corporate finance, or related roles
- Demonstrated expertise in advanced modeling, forecasting, and business partnership
- Strong proficiency in Excel
- Proficiency in financial planning tools such as Adaptive, or other similar tools
- Ability to analyze and synthesize large and complex datasets
- Strong business acumen and ability to influence strategic decisions
- Effective communication and executive-level presentation skills
- Ability to operate independently in complex and ambiguous environments
- Strong stakeholder management and cross-functional collaboration skills
- Experience in SaaS or financial technology environments (desired)
- Experience supporting executive leadership and board-level reporting (desired)
Responsibilities
- Serve as the trusted finance partner to CXG leaders by maintaining regular, open communication and guiding budget and resource decisions
- Connect financial data to CXG strategy by advising on trade-offs across capacity, hiring, and go-live priorities
- Coordinate the forecasting of go-lives by partnering with the implementation team, translating capacity, bookings and current backlog into a defensible, time-phased launch forecast
- Support executive-level reporting by preparing materials and delivering insights on go-lives, backlog, and ARR for senior leadership and board discussions
- Ensure alignment of CXG metrics and data sources across Finance and CXG by establishing shared definitions and a single source of truth
- Collaborate with CXG, Accounting and the broader FP&A team by keeping forecasts, actuals, and revenue recognition aligned
- Enhance go-live and capacity forecasting by improving automation, scalability, and data integrity across CXG models
- Champion and help develop AI-led processes to drive efficiencies and shift focus from manual work toward high-value analysis
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