SVP, Marketing Sciences Greater New York City, NY Area

About the role

Mile Marker is an omni-channel agency that combines media, creative, and data to accelerate growth for enterprise brands. Central to our growth strategy is Relay, our proprietary measurement and intelligence platform. Relay powers a closed-loop data flywheel that combines creative and channel impact modeling, normalized data enrichment, and continuous learning to ensure every campaign makes the next one smarter.

We are seeking an executive leader for a newly created role: Senior Vice President, Marketing Sciences.

As we scale, you will build and lead our Marketing Sciences practice alongside our analytics and reporting functions. You will own the methodology, validation, and commercial value of Relay, driving our firmwide AI readiness and client effectiveness frameworks. Partnering directly with our SVP of Engineering (who owns platform architecture), you will own the “what” and “why” of our advanced analytics narrative.

Key Responsibilities

End-to-End Measurement Methodology & Standards

Oversee end-to-end methodologies across Marketing Mix Modeling (MMM), incrementality testing, experimental design, geo/DMA lift, Multi-Touch Attribution (MTA), forecasting, and non-experimental causal inference.

Establish rigorous model validation, back-testing, and documentation frameworks to ensure any model can withstand intense client-side or third-party audit scrutiny.

Manage the ongoing calibration loop between modeled predictions and empirical experimental results.

Set and enforce firmwide measurement standards—defining what the agency will and will not claim regarding marketing effectiveness, and why.

Relay Capability & Commercialization

Define what Relay must produce for growth-stage and enterprise clients, as well as internal client solutions teams (including our Creative Center of Excellence).

Establish the commercial proposition for Relay-as-a-Service and outsourced data enrichment, converting flywheel assets into contracted recurring revenue.

Validate the compounding data claim by publishing defensible methodologies and measured case studies capable of surviving aggressive pitch environments and diligence rooms.

Champion AI readiness, adoption, and evolution across Mile Marker, validating analytical applications and embedding AI workflows into measurement practices.

Organizational Leadership & Team Growth

Lead, restructure, and expand an established analytics organization of seven professionals.

Clearly delineate traditional reporting/analytics from advanced marketing science, staffing each functional track with the right candidate profiles.

Coach, train, and upskill team members to build a collaborative, high-performing culture focused on technical rigor and innovation.

Client Impact & Strategic Thought Leadership

Translate complex mathematical outputs—such as attribution curves, Bayesian contribution decompositions, and scenario forecasts—into strategic recommendations for non-technical executives and CMOs.

Partner with client leads to guarantee every account receives the strategic "so what" behind campaign performance data.

Lead the marketing science narrative in new business pitches, presenting learning agendas, measurement frameworks, and Relay’s capabilities against competitive measurement vendors.

Act as Mile Marker’s primary internal and external spokesperson on measurement through published methodologies, industry speaking engagements, and sector thought leadership.

Qualifications & Requirements

12+ years of total analytics/media experience, with 5+ years hands-on in measurement methodologies and 5+ years leading data/analytics teams.

Proven history of personally building and defending Marketing Mix Models (including Bayesian approaches, adstock/saturation transformations, Ridge regression, and out-of-sample validation).

Expert proficiency in SQL, as well as Python or R.

Familiarity with visualization/data tools (Looker, Funnel, Snowflake) and modern measurement platforms (Measured, Northbeam, Recast, Triple Whale, Prescient).

Experience designing incrementality frameworks (geo holdouts, conversion lift) and causal inference techniques (synthetic control, diff-in-diff).

Demonstrated experience monetizing analytical assets or productized agency data services.

Advanced degree in a quantitative field (Statistics, Mathematics, Computer Science, Economics, or related).