Marketing Data Science Manager Position

:JD We are hiring a Marketing Data Science Manager to leverage analytical frameworks and predictive modeling for actionable marketing insights and campaign optimization. The position is virtual, preferably aligned to the AZ time zone, with a full-time schedule. Multiple virtual interviews will be part of the process. Key Requirements • Education: Bachelor’s or Master’s in Statistics, Economics, Marketing Analytics, Computer Science, or related fields. • Experience: • 10+ years in machine learning, marketing analytics, statistical modelling, and marketing mix modeling. • 10+ years applying regression analysis, time series analysis, predictive modeling, and optimization. • 7+ years with statistical software: SQL, R, Python, Power BI. • 5+ years with AWS Sage maker, Lambda, marketing research tools/methodologies. • Terraform experience preferred. Skills: • Proven ability to translate data/model outputs into actionable business and marketing strategies. • Strong problem-solving and attention to detail. • Track record of clear, concise communication with technical and non-technical stakeholders. • Collaborative mindset with cross-functional teams (media, creative, product, finance). • Good to have: • Experience in AI/multi-touch attribution models, ad platforms (Google Ads, DV360), A/B testing, and experimentation frameworks. Advanced Skills • Model development, deployment, and optimization in AWS (Sagemaker, EC2, S3, Terraform, Bitbucket). • Data integration and modeling using SQL, Python, R. • Analytics/visualization with Power BI, Excel, streamlit. • MMM, optimizer applications; building scalable analytics pipelines (Python/R, SQL, cloud platforms). Key Responsibilities • Develop and deploy predictive/statistical models to evaluate marketing performance (attribution, MMM, churn, LTV, segmentation, optimization). • Translate modeling results into business recommendations and present findings using storytelling and visualization tools. • Build and maintain analytics pipelines; operationalize insights for audience targeting and spend optimization. • Partner with marketing operations, data engineering, and analysts to improve data accessibility and accuracy. • Monitor model performance, improve simulation/optimization apps, and push updates to production. • Handle ad-hoc data requests, exploration, and intelligent dashboard creation. • Collaborate cross-functionally, provide documentation and internal trainings, and manage project timelines and deliverables. • Support experiment design, ROI measurement, and strategy development with marketing/product teams. Benefits & Opportunities • Direct impact on shaping the marketing data science/insights function. • Influence marketing strategy and customer growth. • Exposure to advanced analytics and experimentation in a data-driven organization. • Career growth and pathway to possible full-time employment.