Digital Marketing Analytics Director - Corporate (Las Vegas or Jersey City)

Caesars Entertainment•Las Vegas, NV

About The Position

WE ARE CAESARS At Caesars Entertainment, our Mission, Vision & Values reflect our unique purpose, providing people with possibilities and places to have fun. Our Mission, Vision & Values represent a unifying and inspiring way forward, and all Team Members are expected to uphold them. Our Mission: “Create the Extraordinary” Our Vision: “We create spectacular worlds that immerse, inspire and connect you. We don’t perform magic; we create it with excellence.” Our Values: “Blaze the Trail, Together We Win, All-In on Service” Our corporate social responsibility framework, People Planet Play, represents our continuous dedication to enhancing economic development, uplifting the wellbeing of our Team Members and their families, and making positive contributions to the communities we operate in. JOB SUMMARY We are seeking a Marketing Analytics Lead who will architect, build, and maintain a daily-updating spend optimization engine that guides how much our marketing team should invest across channels (e.g., paid social, affiliate, search, programmatic) and within each channel (e.g., Meta vs. Snapchat vs. Reddit). HOW YOU WILL CREATE THE EXTRAORDINARY Design and implement a daily-refreshing spend allocation model that integrates performance data, incrementality signals, and budget constraints. Develop logic to recommend optimal channel- and sub-channel-level spend based on performance, saturation curves, marginal ROI, and forecasted outcomes. Create dashboards, APIs, or automated reports that surface recommendations to the marketing organization in a clear, actionable format. Build and maintain data pipelines that ingest data from ad platforms, MMPs, internal databases, and attribution systems. Ensure data quality, freshness, and model reliability through automated checks and monitoring systems. Develop or refine Media Mix Models (MMM) , incrementality frameworks , marginal return curves , and/or bid/optimization simulations . Partner with finance, marketing, and product to integrate non-marketing factors (seasonality, product promos, inventory, etc.) into spend recommendations. Serve as the analytical thought leader for marketing investment decisions. Work closely with channel owners to ensure recommendations align with campaign strategy and creative cycles. Collaborate with engineering to productionize models and maintain scalable infrastructure. Lead A/B tests and incrementality experiments to improve the accuracy of spend recommendations. Iterate on the model as new channels, geos, or strategies come online.

Requirements

Must be 21 years of age or older
5+ years in marketing analytics, data science, growth analytics, or similar.
Strong proficiency in Python or R , SQL, and scalable model deployment workflows.
Experience building MMM , incrementality tests , or ROI/attribution models .
Knowledge of paid media channels (paid social, search, affiliate, programmatic, etc.) and their underlying mechanics.
Experience with visualization tools (Tableau, Power BI, Looker) for delivering insights and automated reporting.
Ability to turn complex modeling outputs into simple business recommendations.

Nice To Haves

Experience with automated decisioning systems (e.g., budget pacing tools, bidding engines, forecasting models).
Familiarity with cloud environments (e.g., GCP, AWS, Azure).
Exposure to Bayesian modeling, causal inference, or machine learning methods used in marketing optimization.
Startup or growth-stage experience where speed and autonomy are valued.

Responsibilities

Design and implement a daily-refreshing spend allocation model that integrates performance data, incrementality signals, and budget constraints.
Develop logic to recommend optimal channel- and sub-channel-level spend based on performance, saturation curves, marginal ROI, and forecasted outcomes.
Create dashboards, APIs, or automated reports that surface recommendations to the marketing organization in a clear, actionable format.
Build and maintain data pipelines that ingest data from ad platforms, MMPs, internal databases, and attribution systems.
Ensure data quality, freshness, and model reliability through automated checks and monitoring systems.
Develop or refine Media Mix Models (MMM) , incrementality frameworks , marginal return curves , and/or bid/optimization simulations .
Partner with finance, marketing, and product to integrate non-marketing factors (seasonality, product promos, inventory, etc.) into spend recommendations.
Serve as the analytical thought leader for marketing investment decisions.
Work closely with channel owners to ensure recommendations align with campaign strategy and creative cycles.
Collaborate with engineering to productionize models and maintain scalable infrastructure.
Lead A/B tests and incrementality experiments to improve the accuracy of spend recommendations.
Iterate on the model as new channels, geos, or strategies come online.