Business Analytics Manager (Finance)

RESPONSIBILITIES:

• Partner with FP&A on topline forecasting, ensuring assumptions are grounded in operational reality and core business drivers are clearly defined and measurable.

• Improve the structure, consistency, and scalability of planning processes across budget, rolling forecast, and long-range planning.

• Establish clear frameworks for pacing and variance analysis that increase organizational accountability and improve forecast precision over time.

• Translate complex business dynamics into structured, decision-oriented insights for senior leadership.

• Partner with Growth and Marketing to ensure initiative-level forecasts align to company targets and reflect sound financial logic.

• Build thoughtful business cases for incremental investments and initiatives, grounded in disciplined, data-driven tradeoff analysis.

• Help leadership understand the financial implications of strategic decisions - balancing short-term performance with long-term value creation.

• Design and institutionalize scalable planning frameworks that improve accuracy and reduce friction across teams.

QUALIFICATIONS:

• 6+ years of experience in Financial Analytics, Strategic Finance, Growth Analytics, or a similarly rigorous role within a subscription, DTC, or consumer technology business.

• Strong financial modeling skills; comfortable building and refining driver-based forecasts that support executive planning.

• Demonstrated ability to deeply understand business models and connect operational drivers to financial outcomes.

• Strong track record building business cases and evaluating strategic tradeoffs using structured analytical frameworks.

• High bar for analytical integrity and a bias toward accuracy over narrative.

• Advanced SQL proficiency required; experience working with complex data models in Snowflake, dbt, or similar environments preferred.

• Strong executive presence; able to defend assumptions and recommendations clearly and confidently.

• Proven ability to align stakeholders with differing priorities around shared, data-driven conclusions.

• Self-starter with a player-coach mentality - equally comfortable shaping strategy and diving deep into the underlying data and models.