Lead, Finance Analytics & Enablement AI/ML

About the role

Hopper is seeking a Lead, Finance Analytics & Enablement AI/ML to manage the data warehouse, business intelligence, GCP/AI optimization, and finance AI enablement strategy. This role requires managing partner relationships across the organization and reporting directly to the Chief Financial Officer.

Responsibilities

• Provide actionable insights to drive business decisions based on finance and data analytics
• Own the data warehouse strategy, governance, and execution of the finance ledger
• Create, own, implement, and track success of the Finance AI automation roadmap in partnership with FP&A, accounting, and data
• Establish data pipeline and AI model foundation
• Optimize GCP infrastructure costs in partnership with engineering and Financial Operations
• Create self-service analytics for key stakeholders
• Manage a team of 4 engineers and 1 finance and strategy manager
• Establish internal controls and support external audits related to data governance
• Work experience 15+ years in travel and/or SaaS
• Bachelor's Degree, with a strong preference for a Master's degree or equivalent experience
• Engineering background preferred
• Fluency in SQL, Python, GCP, and Data Science, hands-on coding ability
• Understanding of LLM-based systems, prompt design, and AI model evaluation frameworks
• Familiarity with automation frameworks and observability tools (Amplitude, Datadog, Looker) to assess reliability and performance
• Strong data reconciliation skills across large, multi-source datasets
• A bias toward first-principles thinking — questioning assumptions, stress-testing processes, and always asking why something works the way it does
• Clear communicator with senior leadership and external partners
• “Comfort with ambiguity and ground-zero building”

Requirements

• Work experience 15+ years in travel and/or SaaS
• Bachelor's Degree, with a strong preference for a Master's degree or equivalent experience
• Engineering background preferred
• Fluency in SQL, Python, GCP, and Data Science, hands-on coding ability
• Understanding of LLM-based systems, prompt design, and AI model evaluation frameworks
• Familiarity with automation frameworks and observability tools (Amplitude, Datadog, Looker) to assess reliability and performance
• Strong data reconciliation skills across large, multi-source datasets
• A bias toward first-principles thinking — questioning assumptions, stress-testing processes, and always asking why something works the way it does
• Clear communicator with senior leadership and external partners
• “Comfort with ambiguity and ground-zero building”

Qualifications

• Background at a high-growth technology or marketplace company
• Experience working cross-functionally with data engineering or warehouse teams

Nice to Have

• Background at a high-growth technology or marketplace company
• Experience working cross-functionally with data engineering or warehouse teams

Benefits

• Well-funded and proven startup with large ambitions, competitive salary and the upsides of pre-IPO equity packages
• Unlimited PTO
• Carrot Cash travel stipend
• Access to co-working space on demand through FlexDesk AND Work-from-home stipend
• Very generous parental leave, much above industry standards
• Entrepreneurial culture where pushing limits and taking risks is everyday business
• Open communication with management and company leadership
• Small, dynamic teams = massive impact
• 100% employer paid Medical, Dental and Vision coverage for employees
• Access to Disability & Life insurance
• Health Reimbursement Account (HRA)
• DCA/ FSA and access to 401k plan