Manager, Marketing Analytics

Executive Reporting and Business Intelligence
Own the executive reporting layer for lead, application, enrollment, start, and persistence performance — including funnel conversion, budget-to-actual, forecast variance, and prior-period comparison.
Lead the build and evolution of Power BI datasets, measures, and dashboards that enable self-service analytics on demand.
Set and enforce KPI and metric definitions across Marketing, Admissions, and Finance, so a given number means one thing institution-wide.
Carry production accountability: refresh monitoring, data availability, and investigation of discrepancies before stakeholders encounter them.
Deliver monthly and quarterly executive readouts that lead with recommendations rather than results.
Own recurring reporting for financial-aid packaging and LDA-based retention tracking alongside acquisition performance.
Marketing Technology and CRM platform ownership
Own administration and governance of the marketing CRM across both the campus and workforce development instances, including consolidating the two into a single supported model.
Own lead routing, lifecycle workflows, automation, and the design of lead management,
scoring, routing, and nurturing.
Own call-tracking administration and its integration into the marketing data layer.
Establish data-quality controls, change management, and system documentation that survive personnel turnover.
Manage martech vendors, agency partners, and integrations; evaluate new platforms including AI-assisted and voice AI workflows.
Partner with IT and Development on marketing data infrastructure and architecture.
Advanced Analytics and Measurement
Direct the move of predictive lead scoring from pilot into production scoring, and the operational workflows that consume it.
Own the marketing attribution model — its development, its limits, and its use in budget allocation.
Lead forecasting, marketing-mix, and acquisition-efficiency analysis in partnership with Finance.
Own experimentation: test design, matched-market and A/B methodology, measurement, and readout.
Direct geographic opportunity and student-distance modeling to guide spend allocation and program planning.
Translate model output into operational recommendations Admissions and Marketing can act on.
Analytics Demand and Cross-Functional Partnership
Own analytics request intake, prioritization, and capacity allocation — and the authority to say no, with a reason and a timeline.
Resolve competing stakeholder priorities across Marketing, Admissions, Campus Operations, Finance, and IT; communicate tradeoffs explicitly.
Translate business questions into analytical and technical requirements.
Serve as the senior analytics voice with executive leadership, agencies, and technology vendors.
Maintain a clear escalation path for data and system issues that previously routed to one person.
Team Leadership, Standards, and Development
Lead and develop the team, supporting defined growth tracks in marketing systems and business intelligence.
Review high-impact deliverables and validate calculations before they are distributed.
Coach the team on SQL, Power BI, and business logic — credibly, from having done the work.
Set reporting standards, metric definitions, SOPs, and documentation practice.
Deliver user training on reporting and CRM systems to Marketing and Admissions staff.
Regular, in-person attendance up to 5 days per week on campus/on site is an essential function of this position.
This role requires on-site collaboration with students, faculty, and staff.
Bachelor’s degree required; advanced degree in a quantitative field preferred.
5+ years in marketing analytics or business intelligence, including 4+ years leading a team.
Hands-on SQL. You write, optimize, validate, and review production queries yourself.
Hands-on Power BI — data modeling, DAX, workspace governance, and refresh and gateway operations.
Direct ownership of a marketing CRM or automation platform as an administrator, not a user — LeadSquared, Salesforce and Marketing Cloud, HubSpot, Velocify, or comparable.
Demonstrated ownership of attribution, forecasting, and acquisition-efficiency or marketing-mix analysis.
Experience designing tests and reading out results to non-technical audiences.
Working knowledge of data science practice — propensity and predictive modeling, applied statistics — sufficient to direct and review a data scientist’s work.
A track record running an intake and prioritization process across departments with competing claims.
Executive presence: able to brief, influence, and disagree with senior leadership productively.
Strong sense of accountability, owning successes and failures.

Employment type
Full-time

Work arrangement
No