Staff Marketing Strategy Analyst

Vanguard • Malvern, PA

1d • Hybrid

About The Position

We are seeking a Staff Marketing Strategy Analyst to drive step-change improvements in marketing performance through advanced analytics, marketing strategy, experimentation design, and predictive/causal modeling. This role operates as an analytical strategist - owning ambiguous, high-complexity problems end-to-end and shaping the analytics agenda across multiple workstreams and stakeholders. The ideal candidate thrives at the intersection of marketing strategy, analytics, and data science—setting direction, aligning partners, and influencing outcomes at all levels of the organization. They can translate complex data into actionable narratives for both technical and executive audiences, ensuring insights are implemented and measurably improve business outcomes. Core Responsibilities (Strategy Design + Analytics and Data Science Execution + Leadership): 1) Own ambiguous, complex problem spaces end-to-end Frame unclear business needs into well-scoped analytical problem statements, hypotheses, and decision pathways Define success metrics, measurement strategy, and evaluation methodology tied to business OKRs Drive work independently across multiple concurrent priorities with minimal oversight 2) Set analytical strategy and scalable frameworks Establish and evolve the marketing analytics framework for optimization, measurement, and experimentation at scale Architect repeatable approaches for: -Enhanced campaign reach and effectiveness -Measurement and experimentation -Incremental lift and causality -Optimization and scenario planning Translate strategy into operational playbooks and scalable “data products” (data blocks, model scores, operationalization pipelines, experimentation standards) 3) Deliver advanced analytics that changes business decisions Lead advanced analyses using statistical modeling, predictive approaches, and experimentation/causal inference techniques to identify drivers of ROI and customer outcomes Perform “what-if” and sensitivity analyses to quantify tradeoffs, risks, and expected impact Diagnose performance issues across funnel stages (awareness → conversion → retention), translating findings into concrete action plans 4) Lead through influence Serve as a strategic connector across Marketing, Sales, MarTech, Data Science, Data Engineering, Data Strategy, and other analytics teams Facilitate alignment on approach, methodology, governance, scope, requirements, and roadmaps Build coalitions, negotiate tradeoffs, and drive decisions when stakeholders have competing priorities 5) Executive-ready communication and storytelling Create crisp, compelling narratives that communicate: -What we learned -What it means for the business -What we recommend -How we will measure impact Present insights to senior leaders and executives; proactively manage risk, uncertainty, and methodology limitations with clarity 6) Raise the bar for analytics maturity Proactively identify opportunities to improve marketing effectiveness through better data, tools, or processes Evangelize data-driven decision-making, strategic thinking, and experimentation best practices across the organization Mentor peers and junior analysts on analytical rigor, storytelling, and stakeholder management Identify capability gaps and propose solutions (tooling, data, operating model, training, governance) What success looks like (first 6-12 months) Establish subject matter expertise in full data ecosystem – internal and 3rd party Established a clear roadmap aligned to marketing OKRs and adoption by key stakeholders Ship at least 1–2 scalable analytics “assets” (e.g., Analytical and Data Science approach and roadmap, Standardized KPI framework, experimentation playbook, Client insights using data, self-serve executive dashboard with ongoing enhancements) that reduce ad-hoc effort and improve decision velocity. Delivered quantified business impact (e.g., improved ROI, conversion, cost efficiency, or incremental lift) supported by robust measurement Built strong cross-functional partnerships and credibility as a go-to analytical leader

Requirements

• 10+ years’ experience within Financial Services, 8+ years’ experience in marketing strategy analytics, with demonstrated progressive scope and influence
• Undergraduate degree in Marketing, Statistics, Data Science, Economics, Applied Mathematics, or related field (Graduate degree preferred)
• Advanced proficiency in SQL and at least one analytics language (Python preferred); strong command of data wrangling and reproducible analysis
• Strong knowledge of: -Experimentation design and evaluation (A/B testing, power, guardrails, inference) -Statistical modeling (regression, segmentation, time series, predictive modeling) -Marketing/funnel KPIs (ROI, LTV, CAC, attribution, engagement, conversion) -Deep understanding of digital marketing ecosystems (channels, platforms, and measurement strategies)
• Proven ability to cross influence across multiple stakeholder groups
• Excellent executive communication—ability to distill complexity into clear decisions and recommendations. Strong deck writing skills to influence senior leadership.
• Entrepreneurial mindset, building and scaling new analytics capabilities from the ground up while balancing innovation, rigor, and enterprise level accountability

Responsibilities

• Own ambiguous, complex problem spaces end-to-end Frame unclear business needs into well-scoped analytical problem statements, hypotheses, and decision pathways Define success metrics, measurement strategy, and evaluation methodology tied to business OKRs Drive work independently across multiple concurrent priorities with minimal oversight
• Set analytical strategy and scalable frameworks Establish and evolve the marketing analytics framework for optimization, measurement, and experimentation at scale Architect repeatable approaches for: -Enhanced campaign reach and effectiveness -Measurement and experimentation -Incremental lift and causality -Optimization and scenario planning Translate strategy into operational playbooks and scalable “data products” (data blocks, model scores, operationalization pipelines, experimentation standards)
• Deliver advanced analytics that changes business decisions Lead advanced analyses using statistical modeling, predictive approaches, and experimentation/causal inference techniques to identify drivers of ROI and customer outcomes Perform “what-if” and sensitivity analyses to quantify tradeoffs, risks, and expected impact Diagnose performance issues across funnel stages (awareness → conversion → retention), translating findings into concrete action plans
• Lead through influence Serve as a strategic connector across Marketing, Sales, MarTech, Data Science, Data Engineering, Data Strategy, and other analytics teams Facilitate alignment on approach, methodology, governance, scope, requirements, and roadmaps Build coalitions, negotiate tradeoffs, and drive decisions when stakeholders have competing priorities
• Executive-ready communication and storytelling Create crisp, compelling narratives that communicate: -What we learned -What it means for the business -What we recommend -How we will measure impact Present insights to senior leaders and executives; proactively manage risk, uncertainty, and methodology limitations with clarity
• Raise the bar for analytics maturity Proactively identify opportunities to improve marketing effectiveness through better data, tools, or processes Evangelize data-driven decision-making, strategic thinking, and experimentation best practices across the organization Mentor peers and junior analysts on analytical rigor, storytelling, and stakeholder management Identify capability gaps and propose solutions (tooling, data, operating model, training, governance)

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level