VP, Analytics

Muck Rack

VP of Analytics leading a team of analytics engineers and business analysts for data-driven decisions at Muck Rack. Shaping analytics infrastructure and ensuring trustworthy data alignment across departments.

Posted 6/2/2026full-timeRemote • 🇺🇸 United StatesLead💰 $250,000 - $300,000 per yearWebsite

ATS Keywords

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Hard Skills

analytics leadershipanalytics engineeringdata modelingsemantic layernatural language queryingB2B SaaSdata productsreport creationAI analyticsbusiness intelligence

Soft Skills

executive presencebusiness acumenstakeholder managementteam buildingprioritizationcommunicationinfluencecustomer focusproblem-solvingcollaboration

Tools & Technologies

dbtSnowflakeBI toolsanalytics toolsdata visualization toolsreporting toolsAI toolsLLM-enabled analyticsdata quality toolsautomation tools

Industry Keywords

embedded analyticshub-and-spoke modeldata stackself-serve analyticsmetric definitionsad hoc requestsinfrastructure investmentbusiness metricspipeline conversionfeature adoption

About the role

Key responsibilities & impact

Define and maintain the single source of truth for every business metric at Muck Rack: from ARR and net retention to pipeline conversion and feature adoption
Own the analytics engineering function: a small, high-leverage team that maintains our dbt project and builds the semantic layer that powers both human and AI-driven analytics and decides how data is modeled, curated and exposed
Set the AI analytics roadmap: architect the path from today’s dashboard-driven reporting toward a natural language, self-service model where stakeholders can query metrics directly
Manage and build a team of embedded business analysts each reporting to you while sitting functionally within their business team
Deeply understand the workflows of each function your team serves. Map out what a CSM does in a given day, week, and quarter. Understand what the best-performing reps do differently. Identify where data and tooling can systematize what great looks like and build it
Treat each department as a “customer” of the analytics team: understand their use cases, anticipate their needs, and proactively build the data products and dashboards that help them perform, rather than waiting for requests
Set quality standards and methodology across all analysts to ensure consistency in metric definitions, analytical rigor, and output quality — regardless of which function they’re embedded in
Build and run the BA community of practice: weekly syncs, peer review, shared learnings, and professional development
Build and operate the prioritization framework that balances the long tail of ad hoc requests against investment in infrastructure, automation, and proactive insight-building
Be the gatekeeper: protect the team’s capacity for high-leverage work (semantic layer, AI tooling, automated reporting) while ensuring urgent business questions still get fast answers
Make the trade-offs visible stakeholders should understand what the team is working on, why, and what’s in the queue
Evaluate and evolve our BI tooling strategy, with a focus on enabling faster, more flexible report creation without tools and dashboards proliferating unchecked
Build the semantic layer as the foundation for consistent metric definitions across every consumption layer including dashboards, ad hoc analysis, and AI agents
Deliver a natural language querying capability that lets executives and operators get quick answers to metric questions without submitting a request.

Requirements

What you’ll need

8+ years of progressive analytics leadership experience, including managing both analytics engineers and business analysts at a B2B SaaS company
Track record of building and scaling embedded or hub-and-spoke analytics models where analysts sit within business functions but report centrally
Deep understanding of the modern data stack. You’ve worked with dbt, Snowflake (or equivalent), and at least one major BI tool. You have a point of view on semantic layers and how they change the analytics operating model
Experience acting as a “product manager” for an analytics function, including mapping stakeholder workflows, proactively building data products, and making deliberate prioritization decisions about where the team spends its time
You’ve managed the tension between ad hoc requests and long-term infrastructure investment, and you have a framework for how to balance them
Demonstrated ability to partner with and influence C-level and VP-level stakeholders across Sales, Finance, Product, and Customer Success, with strong executive presence and business acumen
Comfort with AI/LLM-enabled analytics. You don’t need to be an ML engineer, but you should have a clear and informed point of view on how AI changes the analytics function and the ambition to build toward it
Strong opinions about BI tooling, data quality, and what “self-serve analytics” actually looks like in practice (not just a buzzword)
You can translate a business question into a data model, and a data model into a business narrative. You’re as comfortable in a board meeting as you are reviewing a dbt pull request
Alignment with Muck Rack’s core values: Customer Devotion, Resilience, Transparency, Ownership
Proactively incorporate AI tools into day to day work to improve productively and accelerate delivery.

Benefits

Comp & perks

Comprehensive medical, dental, vision, disability, and life insurance for employees and dependents
100% premium coverage for individuals on high-deductible plans
24/7 Virtual Care and Employee Assistance Program
Employer-funded HSA contributions and other pre-tax benefits
Quarterly wellness stipend and free Headspace subscription
4+ weeks of PTO, plus paid sick and mental health days
13 paid holidays with the option to swap for personal days
Up to 16 weeks of fully paid parental leave
Transparent pathways for internal mobility and promotion
Bi-annual performance reviews, team workshops, and leadership training
Unlimited access to Coursera and O’Reilly
2 additional PTO days annually for learning and development
Commitment to equity and valuing diverse perspectives
Agile, founder-led company focused on collaboration and innovation
Fully distributed team with a permanent remote setup