Director, Marketing Science

About Measured

Measured is the pioneer and leader of incrementality-based media measurement and optimization. Since 2017, leading brands have used our AI-powered, all-in-one platform to manage, test, plan, and optimize over $35 billion in full-funnel media investments. Measured’s unique combination of automated experimentation, media mix modeling, and industry-leading expertise helps marketers prove the incremental impact of their advertising and maximize ROI with unmatched ease, accuracy, and efficiency.

The Role

Measured is seeking a Director of Marketing Science: a n expert in marketing measurement and incrementality who builds the systems and provides the expertise that let a small team, amplified by AI, deliver measurement quality at scale across our entire client base. This is a hands-on, non-dedicated role. You will not be assigned a book of accounts. Instead, you will build the automation and set the standards that lift every model, and step in on the hardest measurement problems as the senior expert.

You bring holistic command of the Marketing Science range: geo-based incrementality experimentation, agile mix modeling for marketing and business analytics, and cross-channel planning and optimization. This role places particular emphasis on enterprise planning and optimization, helping brands turn incrementality into cross-channel budget decisions, while drawing on the full measurement toolkit to do it well.

Marketing Science sits between Data Science and Customer Success. We manage the modeling systems Data Science builds, explain how results are produced and what they mean, and build the tooling that lets us do both at scale. A central objective of this role is to apply AI to solve complex measurement and planning questions systematically, so that solutions compound into repeatable capability rather than one-off answers.

The role operates in three modes: build the AI-driven automation that handles the first pass at scale; own and continuously shrink the model-management and planning queue; and support client teams by exception, routed through Customer Success, as the senior measurement voice, escalating only genuinely novel work to Data Science.

At Measured, we equip every team member with best-in-class technology to fuel extraordinary outcomes. We expect our team to continuously evolve alongside these tools, using AI as a partner for momentum and innovation — raising the bar on everything we build. Our people own the final voice, judgment, and accountability behind every deliverable.

Requirements

Key Responsibilities

Build AI-Powered Automation and Agentic Workflows

• Build scalable, AI-driven solutions across the Marketing Science range: geo-based incrementality experimentation, agile mix modeling, cross-channel planning and optimization, and model-health monitoring.
• Design and ship agentic workflows for first-pass diagnosis, plan generation, model management, and insight generation, built in partnership with Data Science and Product rather than in isolation.
• Replace manual, labor-intensive processes with automation that holds up under scale, and codify recurring solutions into repeatable, reusable capability rather than one-off answers.
• Prototype and build with modern AI tooling (LLMs, Claude Cowork, Claude Code, and similar).

Apply the Full Measurement Toolkit, with a Focus on Enterprise Planning and Optimization

• Bring depth across geo-based incrementality testing and agile mix modeling, applying the right method to answer the marketing and business-analytics questions clients actually face.
• Focus in particular on enterprise planning and optimization: translate incrementality-based response curves, saturation, and marginal returns into cross-channel budget plans clients can act on.
• Build and scale the automation behind planning workflows, including scenario simulation, constraint setting, and tie-out to committed budgets, so enterprise-grade planning becomes repeatable rather than bespoke.
• Serve as the senior resource on complex optimization questions, from constrained scenarios and flighting to reconciling planned versus in-flight performance.

Own the Scaled Model-Management Function

• Run the standing scaled desk for calibration, drift, and configuration exceptions across the full portfolio, prioritized worst-first by model health rather than by account.
• Triage the incrementality, mix-modeling, and planning queues, automate the recurring first pass, and equip Customer Success with the playbooks and permission to handle the routine.
• Define the onboarding and setup-QA standard that stops issues at the source, so the team spends less time fixing models that were never set up correctly.

Analytical Resource and Expert Voice of Measurement

• Serve as the go-to analytical resource for client-facing teams on complex measurement and planning questions that go beyond the standard workflow.
• Explain experiment, model, and plan results, and the business implications behind them, in clear terms; isolate media drivers and provide the “why behind the what,” including across emerging platforms like Google Performance Max (PMax) and Meta ASC.
• Join high-stakes client calls, QBRs, and renewal discussions by exception, as the senior measurement expert, without being embedded in any single account.

Model Management, Interpretation, and the Data Science Bridge

• Act as the bridge between Data Science and Customer Success: explain how results were produced and what they mean.
• Manage and maintain the modeling systems Data Science has built, and support Customer Success in turning incrementality, mix-modeling, and planning results into recommendations.
• Develop the logic and rules that inform customer-facing tools, and pioneer solutions that eventually shape product innovation at Measured.

Cross-Functional Partnership

• Work closely with Customer Success, Data Science, Product, and Engineering to improve the Measured experience today and build a better Measured for the future.
• Identify the difficult, commonly recurring measurement and planning questions, pioneer solutions, and scale them into a repeatable offering.

Ideal Experience

• Deep, hands-on knowledge across g eo-based incrementality experimentation and mix modeling (MMM), applied to marketing and business analytics.
• 6+ years in marketing measurement, data analytics, media science, or a related technical field.
• Deep, hands-on knowledge across geo-based incrementality experimentation and mix modeling (MMM), applied to marketing and business analytics.
• Strong experience with cross-channel media planning and budget optimization, including response curves, saturation and diminishing returns, marginal ROAS, scenario planning, and real-world planning constraints.
• Strong background in statistical techniques (e.g., causal inference, regression modeling, A/B testing).
• Hands-on experience building with AI tooling (LLMs, agentic frameworks, AI coding and workflow tools) to automate analytical work.
• A builder’s instinct: motivated by creating leverage and systems that scale, rather than owning a book of accounts.
• Experience with digital media platforms (e.g., Google Ads, Meta, TikTok) and performance metrics.
• Ability to tell a compelling story from data, especially to non-technical audiences.
• Strong written and verbal communication and executive presence.
• Bachelor’s or Master’s in a quantitative field (e.g., Statistics, Computer Science, Marketing Analytics).
• Confident decision-maker able to take calculated risks and navigate ambiguity.
• Able to operate autonomously while contributing within a collaborative team.
• Comfortable with rapid change.
• Leads with integrity and embraces diversity in all forms.

Preferred

• Proficiency in Python and SQL is a plus, though not required.
• Hands-on knowledge of building and running media campaigns.
• Prior experience in a startup or fast-paced environment.

Benefits

• 100% Remote
• Competitive Total Rewards and flexible paid time off
• Opportunities to give back through Measured for Good
• Engaged, diverse, and curious culture
• Award-winning technology powered by an agile, collaborative team