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About
What you’ll do
Own the data and metric definitions
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
Lead embedded business analysts as their “product manager”
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
Manage the intake and prioritization of analytical work
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
Drive the BI and AI analytics strategy
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
How success will be measured in this role
Every department leader says they have better, more reliable data support than they did 6 months ago
The company operates from a single, trusted set of metric definitions — no more “my number says X but your number says Y”
Key company input metric readings are automated and delivered on time every week, with minimal manual effort
The semantic layer covers the top 30+ business metrics and is actively used by analysts and (over time) AI agents
Ad‑hoc request turnaround time decreases as self‑serve capabilities and proactive analytics increase
The embedded BA model produces measurable improvements in the functions they serve — better pipeline forecasting, earlier churn identification, more efficient marketing spend
The team ships AI analytics capabilities (natural language querying, automated variance commentary) that reduce manual reporting burden
If the details below describe you, you could be a great fit for this role
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
Nice to haves
Background in or exposure to media, PR, communications, or content‑oriented businesses
Experience evaluating or leading a BI tool migration (e.g., from Looker to Hex, or from dashboard‑heavy to semantic‑layer‑first architecture)
Hands‑on experience with dbt Semantic Layer, MetricFlow, or similar metric definition frameworks
Experience building AI‑powered analytics tools (text‑to‑SQL agents, automated reporting, anomaly detection)
Interview Overview
Intro call with a member of our Talent Team
A video interview with the CFO/COO
A case exercise: given a sample business scenario and dataset, walk us through how you would structure the analytics support, prioritize requests, and build toward proactive insight delivery
Panel interviews with members of the executive team and key cross‑functional stakeholders
Travel & Team Engagement Expectations This role requires up to 10% travel for team collaboration, customer engagements, and company events. As part of our commitment to building strong connections across our fully distributed team, attendance at our annual company offsite (typically held in Mexico) is expected.
Salary In the US, the on target earnings for this role is $250,000 – $300,000, depending on skills and experience. Total compensation for this role consists of base salary, bonus, and equity. We take a geo‑neutral approach to compensation within the US, meaning that we pay based on job function and level, not location.
Individual compensation decisions are based on a number of factors, including experience level, skillset, and balancing internal equity relative to peers at the company. We expect the majority of the candidates who are offered roles at our company to fall healthily throughout the range based on these factors. We recognize that the person we hire may be less experienced (or more senior) than this job description as posted. If that ends up being the case, the updated salary range will be communicated with you as a candidate.
EEO Statement Muck Rack considers applicants for all positions on the basis of merit, qualifications, and business needs, and without regard to race, color, national origin, religion, sex, age, disability, sexual orientation, gender identity, alienage or citizenship status, ancestry, marital status, genetic predisposition or carrier status, veteran status, familial status, status as a victim of domestic violence, or any other status or characteristic protected by applicable federal, state, or local law.
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Languages
- English
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