Director, Marketing Investment + Effectiveness (Remote)

Responsibilities

• Lead the FES marketing budget with Finance: total envelope, annual plan, quarterly phasing and the reforecast cycle.
• Own the FES investment plan presented to the SVP and executive team: how much we spend, the brand versus performance split, the expected return on each, and the risks.
• Set the brand and performance envelopes, and the return guardrails each must meet (e.g. blended CAC and payback for performance; reach, awareness and demand for brand).
• Decide in-year moves between brand and performance, using portfolio-level response curves and marginal rather than average return.
• Own the marketing mix model (in-house or vendor): design, calibration with experiments and falsification checks, as the single source of truth for the incremental return of brand and performance spend.
• Own the FES test agenda and governance: incrementality tests prioritized by budget at stake, pre-registration, power and sample size, no early looks before the registered read, decision rules (scale, hold, cut) and a shared log of results. Test cells are designed with the teams that run the media.
• Set FES metric standards (blended versus paid CAC, value windows, denominators) so the investment plan, the scorecard and team reporting all use the same reconciled numbers.
• Build and lead the team, starting with hiring the Manager, Marketing Investment + Effectiveness.
• Partner with Data Science and Analytics on cohort value models and early value signals, and on what they can and cannot support.

Requirements

• Significant experience leading marketing budgets, investment planning or marketing effectiveness at a consumer business, agency or consultancy.
• Track record of setting brand versus performance splits and defending them with Finance and senior leaders.
• Hands-on experience building or managing marketing mix models and incrementality experiments, including geo tests.
• Strong financial planning and modeling skills: budgets, reforecasts, unit economics and payback.
• Strong grounding in causal inference and statistics, and the judgment to know when a result is not strong enough to act on.
• SQL required; Python or R strongly preferred.
• Experience building and leading analytical or planning teams.
• Excellent executive communication, including explaining uncertainty plainly.
• Hands-on, everyday user of AI tools (e.g. Claude, ChatGPT) to work faster and better, and curious about new ways to apply them.
• Background in marketing finance, marketing science or strategy; consumer app experience a plus.