Senior Director, Channel Marketing Analytics

Risepoint

15d

About The Position

Risepoint is an education technology company that provides world-class support and trusted expertise to more than 100 universities and colleges. We primarily work with regional universities, helping them develop and grow their high-ROI, workforce-focused online degree programs in critical areas such as nursing, teaching, business, and public service. Risepoint is dedicated to increasing access to affordable education so that more students, especially working adults, can improve their careers and meet employer and community needs. The Impact You Will Make Risepoint is seeking a Senior Director of Marketing Analytics to lead the analytical strategy, measurement frameworks, and insight generation that drive performance across our paid, organic, email, and field marketing channels. This leader will serve as the primary strategic partner to Channel Marketing leadership—shaping hypotheses, guiding investment decisions, and delivering the rigorous measurement, testing, and insights needed to maximize ROI and accelerate growth. This role will oversee the development of best-in-class attribution, experimentation, and incrementality frameworks; deepen understanding of channel performance drivers; and create actionable recommendations that improve efficiency and effectiveness across the full marketing funnel. The ideal candidate combines strong technical fluency, exceptional business partnership, and a bias toward operational impact—translating complex analyses into clear narratives that shape strategy and outcomes. What You Will Do 1. Strategic Partnership & Insight Leadership • Serve as the senior analytics leader partnering directly with Channel Marketing executives to shape strategy, optimize investment, and identify growth opportunities. • Translate complex channel performance data into actionable insights, elevating understanding of funnel dynamics, ROI drivers, and emerging performance patterns. • Challenge assumptions, frame hypotheses, and guide the team toward the highest impact questions; influence prioritization of campaigns, budgets, and channel mix. • Deliver compelling, executive-ready narratives that support decision-making for business reviews, priority-setting, and investment planning. 2. Lead Measurement, Testing, and Attribution Excellence • Own measurement frameworks including attribution, incrementality, causal inference, and experimentation. • Build and scale test-and-learn practices—A/B testing, geo experiments, MMM enhancements, creative testing, and more. • Develop frameworks quantifying true lift and channel contribution to guide investment with confidence. • Partner with data engineering and BI teams to strengthen data quality, instrumentation, and analytical readiness. 3. Drive Channel Optimization & Performance Insights • Lead analytics informing targeting, bidding strategies, creative performance, spend allocation, and engagement patterns. • Surface proactive insights on saturation, marginal returns, audience behavior, and channel scaling thresholds. • Analyze competitive, seasonal, and external factors to contextualize channel performance. • Build forecasting and scenario models supporting budget and investment decisions. 4. Build and Develop a High-Performing Marketing Analytics Team • Lead, mentor, and grow a team of analysts; elevate technical depth, rigor, and business acumen. • Establish shared methodologies, analytical standards, and scalable processes. • Create a culture of curiosity, innovation, and insight-to-action across the team. 5. Modern Analytics & AI-Enabled Insight Generation • Apply AI/ML techniques—including uplift modeling, creative intelligence, and predictive bidding—to identify new optimization levers. • Leverage GenAI tools to accelerate exploratory analysis, automate insights, and enhance storytelling. • Collaborate with engineering to ensure analytics models and workflows are production-ready and continuously improved. What Success Looks Like • Marketing Analytics is a trusted strategic partner to Channel Marketing. Channel leaders rely on this role to shape investment decisions, challenge assumptions, and translate performance data into clear guidance on where to spend, scale, or pull back. • A clear, shared framework exists for measuring channel effectiveness. The organization has an aligned approach to evaluating efficiency, conversion, and incremental impact across channels—replacing fragmented or directional views with consistent, decision-ready measurement. • Attribution and incrementality thinking meaningfully evolves. The team moves beyond last-touch and surface-level metrics toward test-and-learn, experimentation, and causal approaches that better quantify true channel contribution. How Impact Will be Measured in the First Year • Adoption of standardized measurement and decision frameworks. Channel teams actively use agreed-upon metrics and methodologies to evaluate performance, guide budget allocation, and prioritize optimization opportunities. • Measurable improvements in marketing efficiency and conversion. Analytics-driven insights lead to tangible gains in cost efficiency, funnel conversion, and ROI across key channels. • Stronger analytics influence on business decisions. Analytics is embedded in planning cycles, reviews, and testing roadmaps, with stakeholders demonstrating increased confidence in insights and recommendations.

Requirements

10+ years of experience in marketing analytics, performance marketing, digital analytics, or data-driven growth roles, with a track record of driving measurable impact across acquisition, engagement, and conversion. Strong understanding of the modern data and mar-tech landscape, with the ability to collaborate with data engineering, BI, and marketing operations to ensure proper instrumentation, tracking, and data quality.
Proven ability to design and operationalize advanced measurement systems, including attribution models, incrementality frameworks, causal inference approaches, geo experiments, and multi-touch testing strategies.
Deep experience partnering with channel marketing leaders to shape strategy, guide investment decisions, and translate data into actions that improve ROI, scale, and efficiency. Demonstrated ability to embed insights into operating rhythms, enabling repeatable decisioning frameworks, channel playbooks, testing cadences, and performance management routines.
Hands-on experience with modern marketing and data ecosystems, including ad platform analytics, marketing automation systems, tracking/tagging infrastructure, and cloud-based data environments.
Demonstrated success building and leading high-performing analytics teams, with experience establishing methodologies, governance standards, and repeatable processes that scale across channels. Comfort operating in ambiguity, using structured thinking, hypothesis-driven approaches, and business judgment to clarify priorities and drive actionable outcomes.
Strong executive-facing communication and influence skills, including the ability to frame hypotheses, shape priorities, and guide senior stakeholders toward insight-backed decisions. Leadership, communication, and stakeholder management excellence, with a proven ability to elevate analytical rigor, mentor talent, and build trust with marketing partners.

Nice To Haves

Great to have: Experience in EdTech, marketplace, or multi-channel performance environments; familiarity with MMM, bidding optimization, revenue forecasting.
Deep expertise in core marketing analytics disciplines, including funnel diagnostics, marginal ROI analysis, campaign optimization, forecasting, MMM, audience and creative analytics, and channel scaling frameworks.
Advanced measurement and testing capabilities, including uplift modeling, incrementality testing, causal inference, quasi-experimental approaches (e.g., diff-in-diff, synthetic controls), and geo-based holdouts.
Hands-on analytical fluency with AI and ML techniques (predictive bidding, clustering, creative intelligence, GenAI insight automation), with the ability to identify and operationalize AI-driven levers that elevate channel performance.

Responsibilities

Serve as the senior analytics leader partnering directly with Channel Marketing executives to shape strategy, optimize investment, and identify growth opportunities.
Translate complex channel performance data into actionable insights, elevating understanding of funnel dynamics, ROI drivers, and emerging performance patterns.
Challenge assumptions, frame hypotheses, and guide the team toward the highest impact questions; influence prioritization of campaigns, budgets, and channel mix.
Deliver compelling, executive-ready narratives that support decision-making for business reviews, priority-setting, and investment planning.
Own measurement frameworks including attribution, incrementality, causal inference, and experimentation.
Build and scale test-and-learn practices—A/B testing, geo experiments, MMM enhancements, creative testing, and more.
Develop frameworks quantifying true lift and channel contribution to guide investment with confidence.
Partner with data engineering and BI teams to strengthen data quality, instrumentation, and analytical readiness.
Lead analytics informing targeting, bidding strategies, creative performance, spend allocation, and engagement patterns.
Surface proactive insights on saturation, marginal returns, audience behavior, and channel scaling thresholds.
Analyze competitive, seasonal, and external factors to contextualize channel performance.
Build forecasting and scenario models supporting budget and investment decisions.
Lead, mentor, and grow a team of analysts; elevate technical depth, rigor, and business acumen.
Establish shared methodologies, analytical standards, and scalable processes.
Create a culture of curiosity, innovation, and insight-to-action across the team.
Apply AI/ML techniques—including uplift modeling, creative intelligence, and predictive bidding—to identify new optimization levers.
Leverage GenAI tools to accelerate exploratory analysis, automate insights, and enhance storytelling.
Collaborate with engineering to ensure analytics models and workflows are production-ready and continuously improved.