hopper - Lead, Finance Analytics & Enablement AI/ML
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 • Background at a high-growth technology or marketplace company • Experience working cross-functionally with data engineering or warehouse teams • Perks and benefits of working with us: • Well-funded and proven startup with large ambitions, competitive salary and upsides of pre-IPO equity packages. • Hopper covers 100% of the premiums for group insurance plan. • Hopper offers life, short term and long term disability coverage. • HSA that covers eligible medical and dental expenses. • All employees and dependents have access to Dialogue’s telemedicine services, anytime, anywhere. • All employees have access to an RRSP plan with automatic pre-tax withdrawals per pay. • Please ask us about our very generous parental leave, much above industry standards!. • Unlimited PTO. • Carrot Cash travel stipend. • Access to co-working space on demand through FlexDesk AND Work-from-home stipend. • Entrepreneurial culture where pushing limits and taking risks is everyday business. • Open communication with management and company leadership. • Small, dynamic teams = massive impact.
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 • Build and lead a Center of Excellence for reporting including owning infrastructure and metrics across finance and the business units • 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 • Understand and optimize our GCP infrastructure costs in partnership with engineering and Financial Operations • Establish Finance as the single source of truth for financial and business performance and 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
Benefits
• L7- Finance - CanadaThe yearly total compensation for this position ranges from 400 000$ to 500 000$ CAD. Base salary will be determined by candidates' relevant qualifications, knowledge, skills and work experience. Total compensation will include a solid base salary and will also include equity (options), potentially a sign-on bonus and other potential incentives as per the "perks and benefits" section. CA$400K – CA$500K • Offers Equity • Compensation will be determined by candidates' relevant qualifications, knowledge, skills and work experience. Total compensation will include a solid base salary and will also include equity (options / RSUs), sign-on bonus and other potential incentives. • Veuillez noter : nous avons établi des limites de candidatures pour ce poste. Il fait partie du groupe de limite de candidatures. Les limites suivantes s'appliquent aux candidatures pour tous les postes de ce groupe : • Les candidats ne peuvent pas postuler plus de 2 fois sur une période de 90 jours pour tout poste du groupe de limite de candidatures. • Les candidats ne peuvent pas postuler à nouveau au même poste dans les 90 jours s'ils ne reçoivent pas d'offre. • Please Note: we have set up limits for applications for this role. It is in the Application limit group. The following limits apply to applications for all jobs within this group: • Application limit • Candidates may not apply more than 2 times in any 90 day span for any job in the Application limit Group. • Application limit • Candidates may not re-apply to the same role within 90 days if not presented with an offer • Upload your resume here to autofill key application fields. • Drop your resume here! • Parsing your resume. Autofilling key fields... • or drag and drop here • A) I am located in the US or Canada and can consistently overlap at least 4 working hours with the Eastern Standard Time (EST) zone. • B) I am located in the US or Canada but cannot accommodate a 4-hour daily overlap with the EST timezone. • C) I am located outside of the US and Canada and can accommodate a 4-hour daily overlap with the EST timezone. • D) I am located outside of the US and Canada and cannot work during EST hours. • A) I have direct, professional experience designing data warehouse architectures, optimizing schemas, managing pipelines, and driving infrastructure projects (like GCP optimization or equivalent) from scratch. • B) I am an end-user of data warehouses (querying data via SQL) and understand the concepts, but I have not built, architected, or optimized the warehouse infrastructure myself. • C) I have managed project timelines for data warehousing teams, but I do not have personal, hands-on engineering experience with data warehouses. • D) I have not worked directly with data warehouse architectures or cloud data infrastructure. • A) I go beyond basic reporting; I routinely use Python/SQL to apply statistical modeling, predictive analytics, or data science methodologies to solve complex business problems. • B) I am highly proficient in standard BI tools (e.g., Tableau, Looker, PowerBI) and data analysis, but I do not use Python or apply data science/statistical models to my work. • C) I am a consumer of BI dashboards and analytics reports to make business decisions, but I do not build the technical analytics models myself. • D) I do not have professional experience in business intelligence, data analytics, or data science. • A) I have practical, technical experience with AI systems, which includes evaluating models, building automated workflows, or designing prompt architectures for LLM-based applications. • B) I use generative AI tools (like ChatGPT or Claude) to help write text or code for my own daily tasks, but I have never architected, evaluated, or engineered an AI system for a business. • C) I have read about AI trends and understand the business use cases, but I have no hands-on technical or engineering experience with AI enablement. • D) I have no professional exposure or technical familiarity with AI systems or LLM architectures. • A) I am highly effective at executing project plans and solving complex technical problems, but I perform best when the high-level roadmap and project scope are already defined by a manager or PM. • B) I can build project plans and manage timelines for a team, but I rely on dedicated technical specialists to determine how to execute the cloud or data engineering components. • C) I thrive in high ambiguity; I have a proven track record of taking vague, high-level objectives, designing the project plan from scratch, and executing the technical milestones completely self-driven. • D) I prefer structured environments with clear, daily tasks and well-defined boundaries, rather than defining my own technical roadmap.
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