Staff Marketing Strategy Analyst
Vanguard, Charlotte, NC, United States
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)
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 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
The ideal candidate will have:
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
Sponsorship Vanguard is not offering visa sponsorship for this position.
About Vanguard At Vanguard, we don't just have a mission—we're on a mission.
To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.
How We Work Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.
#J-18808-Ljbffr
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)
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 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
The ideal candidate will have:
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
Sponsorship Vanguard is not offering visa sponsorship for this position.
About Vanguard At Vanguard, we don't just have a mission—we're on a mission.
To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.
How We Work Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.
#J-18808-Ljbffr