• Lead the design and implementation of next-gen media measurement and optimization capabilities, integrating marketing mix, long term brand equity measurement, in-flight measurement (e.g., lift studies, A/B testing), pre-market factors that affect media (e.g., creative testing) • Develop media-driven volume forecasting tools to integrate into McCormick’s demand forecasting platform • Drive and leverage external connections to find new and improved tools and approaches to bring into McCormick • Partner with vendors used for outsourced models, serving as lead consultant on technical methodology alignment integration with new capabilities • Develop training content that enables business partners to use marketing optimization capabilities more effectively

• Lead and execute data science projects, including predictive modeling, algorithm design, and data pipelines; • Develop innovative, industry-leading campaign data science models, specifically partisanship and turnout models; • Independently (and often collaboratively) explore data sets for insights and understanding what can help drive product development and feature prioritization; • Transform data into actionable and compelling insights through analysis and visualization, and then effectively communicate these data-driven stories to internal and external stakeholders through memos and presentations; • Collaborate with the Engineering Team to take data science products and concepts into production; • Provide guidance and mentoring to level-up junior data scientists in both formal and informal learning sessions; • Apply emerging AI technologies to R&D challenges; you’ll prototype novel approaches, evaluate feasibility, and bridge the gap between cutting-edge capabilities and practical usability.

• Develop and deploy analytical models on data and processes to generate insights, support automation, and improve decision-making. • Collaborate with digital product teams and internal stakeholders to shape, enable, and migrate production workflows. • Apply statistics, artificial intelligence, and machine learning techniques to large data sets. • Use multiple programming languages and data transformation tools to support model development and analysis. • Work with databases, data structures, and data architectures to support scalable analytical solutions. • Create visualizations, presentations, and clear quantitative summaries for technical and non-technical audiences. • Explore and adopt new technologies provided by IT engineering and cybersecurity teams. • Work independently with limited supervision while maintaining strong attention to detail and effective team collaboration. • Mentor junior cyber data scientists.

• Developing credit scoring, affordability, and behavioural models to support underwriting, pricing, and collections • Design and run experiments to optimise approval rates, loss rates, and profitability • Partner with product squads to embed decision logic into real-time systems • Ensure data quality, compliance, and ethical use of models across all decisioning processes • Mentor product squads on best practices in experimentation and data-driven decision making • Provide models to optimise outcomes in collections, churn management and user retention