VP, Analytics
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Job Description
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.
Responsibilities:
- 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:
- 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:
- 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
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