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The Coca-Cola Company · 1 day ago

Sr Director I, Modeling and Measurement

Atlanta, GA

Full-time

Onsite

Director/Executive

$189K/yr - $217K/yr

12+ years exp

The Coca-Cola Company is a leading beverage corporation, and they are seeking a Sr Director of Modeling and Measurement to lead the development of advanced marketing measurement frameworks and predictive modeling capabilities. This role involves overseeing a team of data scientists, collaborating with cross-functional partners, and ensuring data-driven decision-making to optimize marketing investments and drive business impact.

Consumer GoodsFast-Moving Consumer GoodsFood and BeverageManufacturing

Comp. & Benefits

No H1B

Responsibilities

Develop & Deploy Measurement Frameworks: Lead the creation of robust marketing measurement frameworks that holistically evaluate the effectiveness of our marketing activations and innovations, including our campaigns and respective channel deployment. Oversee the design and implementation of unified metrics and methodologies – for example, marketing mix modeling (MMM), multi-touch attribution, brand lift studies, and test-and-learn experiments – to quantify marketing impact on key outcomes like sales, brand equity, and engagement. Ensure these measurement systems are fit-for-purpose for NAOU’s needs, integrating both traditional and digital metrics, and that they are consistently applied across brands and initiatives to enable apples-to-apples comparisons

Drive Advanced Predictive Modeling: Guide the development of advanced analytic models to inform marketing strategy and optimization. This includes directing efforts in predictive and prescriptive modeling, such as marketing mix models, consumer segmentation and propensity models, campaign response models, and forecasting tools. Make sure the models are rigorously validated and calibrated to our business context, so they provide reliable forward-looking insights. Leverage these models to identify drivers of performance and recommend allocation of spend (e.g., optimal media mix, targeting strategies) to maximize ROI. Stay at the forefront of analytical techniques (e.g. machine learning, AI) and champion their application in solving marketing problems

Cross-Functional Insight Integration: Act as the key interface between the Data team and the broader marketing organization to turn analytics into action. Collaborate with Media, IMX, Brand, Innovation, Commercial, and Finance teams to ensure modeling and measurement outputs are embedded into planning and decision processes. For example, work closely with Media and IMX directors to inject model findings into campaign planning and in-flight optimizations, so that media plans and creative strategies are continually refined based on data

Partner with Brand and Commercial leads to translate insights into business terms and tactical recommendations (e.g., how a predicted trend or measurement result should adjust a promotion or distribution tactic). By forging these partnerships, ensure that your team’s analytical work is addressing real business questions and that stakeholders understand and leverage the insights for better outcomes

Build & Lead the Modeling/Measurement Team: Recruit, develop, and inspire a high-performing team of data scientists, modeling analysts, and measurement specialists. Provide day-to-day leadership and mentorship, setting and aligning clear objectives with the wider Marketing community and Human Sciences and Advanced Analytics function. Maintain high standards of analytical rigor and business alignment. Foster an environment of continuous learning and innovation, where the team experiments with new data sources, tools, and techniques to improve our marketing intelligence. Ensure the team works seamlessly with IT/Digital Technology (for data engineering, tools, and platform support) and with Analytics/Insights partners (for knowledge sharing and avoiding duplication). Identify skill gaps and invest in capability building (training, best practice development) to keep the team’s expertise cutting-edge

Steer Data Governance & Quality for Analytics: Provide thought leadership and oversight in the required data foundation for marketing modeling and measurement, in partnership with the Data Governance and IT teams. Ensure that data inputs feeding models (e.g., spend data, consumer data, sales figures, media performance metrics) are accurate, consistent, and well-governed. Advocate for any data improvements or integrations needed – for example, connecting new data sources (like a loyalty database or third-party syndicated data) into our analytics environment. Implement processes for ongoing data quality checks and model performance monitoring, so that insights remain reliable over time. Also, maintain documentation and standards for modeling and measurement approaches, contributing to an analytical knowledge base for NAOU Marketing

Innovate and Evolve Analytics Approaches: Continuously evaluate the effectiveness of our modeling and measurement efforts and drive enhancements. Stay informed on industry best practices, emerging marketing analytics technologies, and competitor capabilities in measurement. Proactively introduce next-generation techniques (for example, cutting-edge AI-driven attribution, media optimization algorithms, or unified marketing measurement that blends MMM and digital attribution) to ensure NAOU keeps a competitive analytical edge. Periodically review and iterate on existing models and frameworks – if something is not capturing reality well (e.g., a model’s predictions diverge from actuals), lead the effort to refine it. Encourage a test-and-learn mentality in the team to pilot new approaches on a smaller scale, prove their value, and then scale them up

Deliver Business Impact & Executive Reporting: Be accountable for translating modeling and measurement outputs into clear, actionable insights that drive business value. Synthesize complex analytic findings into simple narratives and visuals for senior leadership, demonstrating how marketing investments are performing and where opportunities exist to improve. Own the creation of regular marketing performance reports or scorecards that incorporate both direct results and modeled insights (e.g., monthly marketing ROI updates, campaign post-mortem reports with key learnings). Present recommendations to senior NAOU Marketing and OU leadership, persuasively advocating for data-backed decisions such as budget shifts or new strategic initiatives. Track the realized impact of changes made based on your team’s analyses (for instance, quantifying incremental revenue gained from a reallocated media plan), and celebrate successes to reinforce the value of the Modeling & Measurement function

Qualification

Marketing mix modelingPredictive modelingData analyticsPython/RSQLData visualizationInnovationLeadershipCommunicationCross-functional collaboration

Required

Bachelor's degree in Statistics, Data Science, Business Analytics, Economics, or a related quantitative field required

12+ years of progressive experience in data analytics, marketing science, or related fields, with a significant portion in marketing measurement and/or marketing mix modeling roles

Proven track record of leading successful analytics initiatives that drove measurable business outcomes in a marketing context

Experience should include hands-on development of predictive models and measurement frameworks, as well as translating analytical results into strategic recommendations at a senior level

Prior experience managing a team of analysts or data scientists is required, with demonstrated ability to mentor talent and build analytical capabilities

Deep understanding of marketing analytics techniques and tools

Mastery of marketing mix modeling (MMM) and other statistical modeling approaches for marketing (e.g., time series analysis, regression, machine learning algorithms for attribution or clustering)

Familiarity with multi-touch attribution models, experimental design (A/B or geo-testing), and marketing KPI frameworks

Strong command of data manipulation and analysis tools such as Python/R, SQL, and advanced Excel; experience with visualization tools (e.g. Tableau, Power BI) for reporting

Ability to oversee model building and validation, and to guide the team in choosing the right methodology for a given business question

Up-to-date knowledge of digital marketing metrics and ad tech (e.g., how to track and attribute digital media performance) is highly valuable

Solid understanding of marketing strategy, consumer behavior, and media fundamentals (across digital, social, traditional channels) to contextualize modeling work

Able to connect the dots between analytical findings and real-world marketing levers

Strong business acumen to focus on analyses that drive profitable growth, and to challenge assumptions that don't align with market reality

Demonstrated success in working cross-functionally – you can speak the language of marketers and translate technical results into the implications for brand managers, media planners, and finance partners

Skilled in gaining buy-in from stakeholders and driving adoption of analytics in decision-making

Excellent leadership skills with experience in building and managing high-performing analytical teams

Capable of setting a vision, prioritizing work (e.g., balancing long-term model development with urgent ad-hoc analysis needs), and delivering results through others

Exceptional communication skills, both in writing and in presentation: able to distill complex analytics into clear stories and business recommendations for senior executives

Comfortable presenting to and persuading senior leadership, and adept at 'telling the story' behind the numbers

A collaborative leader who can influence without authority and foster a data-driven culture across the organization

Passion for staying current with new techniques in data science and measuring marketing in new, innovative ways

Curious and proactive mindset – always seeking better ways to solve problems and not afraid to challenge the status quo

Experience leading change or transformation in how an organization uses data is a plus (e.g., implementing a new analytics tool or rolling out a new measurement process)

Highly adaptable, with the agility to pivot strategies based on evolving business needs or external environment changes

Committed to continuous learning, both for yourself and for uplifting the skills of your team, to keep the organization at the forefront of marketing analytics excellence