AVP, Head of Marketing Analytics & Decision Science (Remote)

Department:
10103 Enterprise Corporate - Consumer Experience, Insights & Analytics
Status:
Full time
Benefits Eligible:
Yes
Hours Per Week:
40
Schedule Details/Additional Information:
Remote
Monday-Friday 8-5pm
Approved remote states: AL, AK, AR, AZ, DE, FL, GA, IA, ID, IL (ONLY Midwest), IN, LA, KS, KY, ME, MI, MO, MS, MT, NC, ND, NE, NH, NM, NV, OH, OK, PA, SC, SD, TN, TX, UT, VA, WI, WV, WY.
Pay Range:
$99.75 - $159.60
AVP, Head of Marketing Analytics
& Decision Science
Build the enterprise decision engine that turns marketing investment into measurable growth and better consumer outcomes.
Join Us in Redefining Care
At Advocate Health, we are committed to helping people live well by delivering exceptional care with compassion, innovation and expertise. We are seeking an enterprise analytics leader to shape how marketing decisions are made, measured and optimized across a large, complex organization.
About This Opportunity
This is a transformational leadership opportunity to move marketing analytics beyond reporting and toward diagnostic, predictive and prescriptive decision support. You will set the enterprise strategy, build an integrated measurement ecosystem and lead a multidisciplinary team that helps senior leaders understand not only what is changing, but why it is changing, what it means and what action to take next.
The mandate: Embed analytics at the front end of marketing and business planning, prove incremental impact, forecast future outcomes and optimize investment using rigorous measurement, experimentation and modern decision science.
What You'll Do
Define and execute the enterprise marketing analytics and decision science strategy, advancing the organization from descriptive reporting to diagnostic, predictive and prescriptive decision support.
Serve as a strategic thought partner at the front end of marketing and business planning by framing business questions, hypotheses, measurement plans and actionable recommendations.
Build an integrated measurement framework spanning marketing mix modeling (MMM), attribution, incrementality, campaign and channel effectiveness, partnerships and sponsorships, in-market testing and marketing ROI.
Establish a rigorous test-and-learn strategy using experimental design, matched-market or geographic testing, holdouts, A/B testing and other causal measurement methods.
Build forecasting and decision science capabilities for scenario planning, demand forecasting, investment optimization, predictive analytics and appropriate AI/ML applications.
Lead data science, analytics engineering and marketing data-product capabilities in partnership with Enterprise Data and Technology, leveraging Snowflake as the enterprise data foundation.
Modernize business intelligence and executive reporting through Power BI and Salesforce Marketing Cloud Intelligence/Datorama, emphasizing decisions and recommendations rather than dashboard production.
Partner with Finance to establish credible methods for connecting marketing activity to consumer, patient, growth and financial outcomes.
Build and lead a high-performing team across decision analytics, business intelligence, marketing measurement, decision science, data science and marketing data products.
Create a culture of curiosity, proactive problem solving and executive-ready storytelling.
What You'll Bring
Bachelor's degree in Analytics, Data Science, Statistics, Economics, Marketing, Business or a related field.
10+ years of progressive experience in marketing analytics, decision science, measurement, data science or a related function, including 5+ years of leadership responsibility in a large, complex organization.
Deep expertise in marketing mix modeling, attribution, incrementality, experimentation, in-market testing and marketing effectiveness measurement.
Strong knowledge of statistical modeling, forecasting, predictive analytics, optimization and data science methodologies.
Demonstrated ability to connect marketing investment to incremental business and financial outcomes and establish credible approaches to marketing ROI.
Strong understanding of modern marketing data architecture, data engineering, analytics engineering, data modeling and cloud data platforms.