Senior Marketing Scientist

Job Description

About Mile Marker:

We are a modern omnichannel agency uniquely connecting data, creative and media to accelerate results for growth marketers. Mile Marker is an agency where content fuels performance, media drives outcomes, and data underpins an engine that eliminates the gaps that slow down enterprise growth marketers. This unified growth engine feeds a learning system within Relay, our open-powered marketing stack, ensuring every impression, message and experience is built for a business outcome. Mile Marker’s client roster includes FreshPet, DoorDash, Spectrum, Webster Bank, TrueGreen, HelloFresh and Harry’s, among others.

We are a team of strategists, media experts, creatives, innovators and analysts. Over 100 Milers (our humans) strong with hybrid-offices in New York City and San Francisco.

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Overview

Mile Marker, an omnichannel media agency built for the ambitions of growth marketers, is seeking a Senior Marketing Scientist to drive the rigor, methodology, and innovation behind our measurement and decision science practice.

This role operates at the intersection of quantitative methodology, data engineering, and growth strategy. As a Senior Marketing Scientist, you will architect advanced measurement frameworks—spanning Econometric Modeling (MMM), Multi-Touch Attribution, and Experimental Design (Incrementality/Geo -Testing)—to help high-growth brands solve complex media allocation and incrementality challenges.

The ideal candidate combines statistical expertise with commercial acumen. You are as comfortable writing production-ready modeling code (Python/R) as you are explaining causal inference concepts to executive client stakeholders.

About the role

We are looking for an applied quantitative practitioner to elevate our agency’s marketing science capabilities. In this role, you will lead the development and execution of sophisticated statistical models, design custom experimentation agendas, and translate complex algorithmic outputs into high-impact growth strategies.

This role’s core focus is scientific rigor, methodology design, and delivering validated incrementality models that directly inform client capital allocation.

Key Responsibilities

Measurement Science & Statistical Modeling

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• Architect, validate, and scale Bayesian/frequentist Marketing Mix Models (MMM) to establish true omni-channel media effectiveness and marginal ROAS curves.
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• Design, execute, and evaluate incrementality frameworks, including Matched-Market/Geo-Experiments, Synthetic Control Methods, and randomized controlled trials (RCTs).
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• Drive methodology for triangulating MMM outputs, attribution models, and experimental results into unified target response curves.
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• Build stochastic forecasting algorithms and lifetime value (LTV) models to optimize budget allocation across portfolio channels.
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Technical Innovation & Analytics Infrastructure

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• Develop reproducible, scalable modeling pipelines in Python or R, maintaining high standards for code quality, version control (Git), and data governance.
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• Custom-build adstock, saturation, and decay functions tailored to unique client buying cycles and macro-economic signals.
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• Collaborate with data engineers to integrate client data warehouses (Snowflake, BigQuery) with Relay, Mile Marker's open-powered marketing stack.
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Strategic Consulting & Commercial Storytelling

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• Bridge the gap between complex quantitative outputs and executive decision-making—translating statistical outputs into clear, actionable budget reallocations.
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• Partner with client strategy leads to draft data-driven Learning Agendas that systematically test incrementality hypotheses.
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• Serve as the subject matter expert in client meetings and pitch presentations, building credibility through methodological clarity and mathematical rigor.
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Thought Leadership & Mentorship

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• Mentor Analysts and Data Scientists in statistical theory, experimental design, Python/R best practices, and model interpretation.
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• Stay at the forefront of marketing science research, continually testing new open-source libraries, causal frameworks, and AI/ML applications in media.
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Desired Skills & Qualifications

Experience

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• 5+ years of professional experience in Marketing Science, Quantitative Marketing, Data Science, or Econometrics, ideally within a high-growth agency, adtech, or direct-to-consumer environment.
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• Degree in a quantitative discipline (Statistics, Econometrics, Applied Mathematics, Computer Science, Economics, or related quantitative field) preferred.
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Technical Requirements

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• Expert-level mastery of Marketing Mix Modeling (MMM), Bayesian statistics, time-series analysis, and causal inference techniques (Matched Markets, Synthetic Controls, Difference-in-Differences).
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• Advanced proficiency in Python (Pandas, NumPy, PyMC, Statsmodels) or R (Tidyverse, Prophet, CausalImpact) for data manipulation, statistical modeling, and automation.
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• Strong proficiency in SQL for querying complex relational databases and cloud platforms (BigQuery, Snowflake, Redshift).
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• Standard workflows using Git/GitHub .
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• Ability to build programmatic visualizations and clear analytical dashboards using tools like Streamlit, Dash, Tableau, or Looker.
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Business & Communication

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• Demonstrated ability to explain complex statistical models, confidence intervals, and incrementality tests to non-technical client executives.
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• Proven track record of translating model outputs into clear budget optimization strategies that increase client ROI and enterprise value.
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