Lead the design, development, validation, and deployment of advanced statistical and machine learning models that power Marketing Mix Modeling (MMM), Multi-Touch Attribution (MTA), audience analytics, and first-party data initiatives, translating complex data into actionable insights that enable data-driven marketing and media investment decisions across the organization.
Develop and refine Multi-Touch Attribution (MTA) models to quantify the incremental impact of digital touchpoints across the customer journey.
Build audience analytics models (segmentation, propensity, lookalike, lifetime value, churn) leveraging first-party data from CRM, CDP, web analytics, and transaction systems.
Translate model outputs into clear insights, dashboards, and storytelling for marketing and media stakeholders, and influence business decisions.
Perform exploratory data analysis and feature engineering on marketing datasets from media platforms, ad servers, and CRM/CDP systems; define data requirements with data engineering teams.
Bachelor's or master's degree in data science, Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.
5+ years of experience in Data Science, Marketing Analytics, or related fields, with hands-on experience building statistical/ML models.
Python (pandas, scikit-learn, statsmodels; PyMC/Stan or open-source MMM libraries such as Robyn/Meridian/PyMC-Marketing preferred) and SQL
Statistical modeling: regression, time series, Bayesian methods
Machine learning: classification, clustering, forecasting, optimization
Cloud platforms: AWS, Azure, or GCP (GCP preferred)
Data visualization and BI tools (e.g., Looker, Power BI, Tableau)
Familiarity with data warehousing and data modeling concepts
Job description provided by Ford Motor Company.
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