Strategic Finance – GTM

Your Impact:
You’ll play a foundational role in building Mercury’s GTM decision engine by:

Building and owning the core datasets that power growth decision-making (e.g., CAC, funnel conversion, cohort performance, LTV inputs, cost-to-serve inputs)
Creating dashboards and tools that enable teams to understand performance across channels, campaigns, and segments
Translating strategic finance frameworks (e.g., payback models, channel scaling rules, ROI thresholds) into scalable systems and decision tools
Designing and implementing automations that reduce manual work, standardize decision-making, and accelerate the path from data, to insights, and then to actions
Partnering with Growth, Marketing, Sales, Partnerships, Product, and Data teams to improve data quality, attribution, and performance visibility
Supporting forecasting and planning processes related to growth and customer behavior
Identifying recurring questions or manual processes and proactively building systems, datasets, or tools to eliminate them

What You Bring:
3–5 years of experience in strategic finance, growth analytics, bizops, or a similar role in a high-growth environment
Strong SQL and data manipulation skills; ability to work directly with large datasets and define clean, scalable data models
Expert modeling skills, including building detailed P&Ls and operating models, with experience building models that are actually used by stakeholders
Experience working on growth, marketing, or customer-related problems (e.g., CAC, funnels, experimentation, or unit economics) is strongly preferred
Strong problem-solving skills with the ability to operate in ambiguity and independently drive problems from definition to a scalable solution
A systems-oriented mindset: you instinctively identify recurring questions or workflows and build scalable solutions (e.g., datasets, tools, automations) to eliminate them
Strong communication skills, with the ability to translate complex analyses into clear, actionable insights
Demonstrated ability to operate in ambiguous environments and translate loosely defined problems into structured, repeatable systems

Our target new hire base salary ranges for this role are the following:

US employees in New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $142,900 – $160,700
US employees outside of the New York City, Los Angeles, Seattle or the San Francisco Bay Area: $128,600 – $144,600
Canadian employees (any location): CAD 135,000 – 151,900