Director, Enterprise Resource Allocation Business Science Intelligence Services Specialist

The Coca-Cola Company•Atlanta, GA

21d•$160,000 - $186,000

About The Position

We’re looking for a Senior Marketing Analytics & Resource Allocation Specialist to help build and scale a global decision‑making platform that guides how marketing and commercial investments are planned, optimized, and evaluated. In this role, you’ll design and deploy advanced analytics—especially Marketing Mix Models (MMM)—to help teams understand what drives growth, how different investments perform, and where resources should be allocated for maximum impact. You’ll work with large, complex datasets and translate sophisticated models into clear, practical recommendations that business leaders can act on. This is a hands‑on role at the intersection of marketing science, data analytics, and business strategy, with the opportunity to influence high‑value investment decisions across markets and regions worldwide. Background & Context Coca‑Cola operates at massive global scale, with brands, bottlers, and markets across more than 200 countries. To operate effectively at this scale, the company is investing heavily in enterprise‑level analytics platforms that help teams make smarter, faster, and more aligned decisions. One of these platforms—Fuelight 360—is a proprietary, end‑to‑end analytics solution designed to: Measure the impact of marketing and trade investments across channels Compare scenarios and trade‑offs before money is spent Align marketing, finance, and commercial teams around a single source of truth Fuelight 360 launched recently and is now moving from early adoption to global scale. This role plays a key part in building the analytics behind the platform, ensuring the models are robust, trusted, and useful for real business decisions. What You'll Do for Us: You will be part of a centralized analytics team that partners closely with regional business units, marketing teams, finance, and technology leaders to bring advanced marketing science into everyday decision‑making.

Requirements

8+ years of experience in marketing analytics, econometrics, marketing science, or a related field
Hands‑on experience building and deploying Marketing Mix Models across multiple channels
Proven ability to translate advanced analytics into business‑ready recommendations
Strong grounding in MMM, ROI optimization, and resource allocation frameworks
Experience with tools such as R, Python, SQL, or similar (coding proficiency is a plus)
Ability to communicate results via dashboards, presentations, or executive‑ready summaries
Understanding of omnichannel marketing measurement
Strong problem‑solver who enjoys turning complexity into clarity
Comfortable working independently in a global, matrixed organization
Confident communicator with senior stakeholders across functions and cultures
Curious, growth‑oriented mindset with a passion for analytics innovation
Bachelor’s degree in Analytics, Data Science, Statistics, Economics, Marketing, or a related field

Nice To Haves

Experience with attribution modeling, causal inference, or scenario planning
Exposure to deploying or scaling analytics platforms or proprietary tools
Master’s degree preferred

Responsibilities

Design and deploy Marketing Mix Models (MMM) that measure marketing effectiveness across paid media, owned channels, earned media, social, and non-media investments (e.g., trade and commerce).
Continuously improve modeling approaches using modern techniques such as Bayesian methods, real‑time data, and evolving MMM frameworks.
Analyze ROI, elasticity, and performance drivers to inform budget allocation and optimization decisions.
Validate model outputs through rigorous analysis to ensure recommendations are credible and actionable
Translate complex analytics into clear, compelling stories for senior leaders.
Support scenario planning, helping teams understand trade‑offs, risks, and upside across different investment choices.
Monitor performance over time and refine models to improve predictive accuracy and business relevance.
Partner closely with product managers, technical teams, and other analytics leaders to ensure insights are embedded into tools and workflows.
Work with marketing, finance, and commercial stakeholders across regions to align on assumptions, insights, and decisions.
Contribute to workshops and training sessions to help teams understand and adopt marketing analytics capabilities.
Help establish best practices and standards for model development, documentation, and deployment.
Explore and pilot new methodologies (e.g., causal inference, next‑generation attribution approaches).
Support the scaling of analytics capabilities across markets, ensuring insights can be operationalized consistently.
Support the Senior Director in scaling processes, ensuring OUs and Bottlers have a clear roadmap for operationalizing marketing insights for business decisions.
Provide technical inputs to upskill functional teams and bottling partners through coaching or training initiatives.