Director of Analytics

Mass Culture

6h•$140,000 - $180,000

About The Position

Mass Culture's model depends on one discipline: knowing what's actually working, and why. The Director of Analytics owns that discipline agency-wide. You will build the measurement infrastructure, attribution models, and reporting standards that turn campaign data into business decisions, for every client, across every channel. This is not a dashboarding role. Clients and leadership come to you for the answer behind the numbers: what's driving growth, what's wasting budget, and what to do next. You will set the analytical standard the entire agency works toward, and make sure every team is making decisions on real signals instead of noise. It is also the role that makes our thesis defensible. We believe brand drives conversion, not the other way around, and we work alongside Brains, a world-class branding agency. Believing that is easy. Proving it is your job. Incrementality tests, geo experiments, holdouts, and media mix modeling are how brand investment earns its budget instead of asking for it on faith.

Requirements

10+ years of analytics, measurement, or marketing data experience, with at least 3 years managing analysts.
Fluent SQL. You can go straight to the warehouse and answer your own question without waiting on anyone.
Proven ability to build and run attribution models, incrementality tests, and cross-channel measurement frameworks in a performance marketing context.
Strong command of analytics and visualization tools (GA4, Looker Studio, or comparable), and the instinct to fix a reporting surface rather than work around it.
Experience translating complex data into clear, business-relevant recommendations for senior stakeholders, including clients. In writing, not just in a room.
A track record of being right in public and wrong in public. We will ask you about a call you got wrong and what you changed because of it.
Practical experience incorporating AI tools into analytical workflows.
Agency environment experience required.

Nice To Haves

Python or R for statistical analysis and automation.
Experience with marketing mix modeling (MMM) or multi-touch attribution (MTA) platforms.
Familiarity with retail media measurement (Amazon Marketing Cloud, closed-loop attribution) and paid social and search platform reporting.
Hands-on experience with cloud data warehouses (BigQuery, Snowflake, Redshift, or Postgres).

Responsibilities

Own agency-wide measurement architecture: attribution models, incrementality testing frameworks, and reporting standards used across every client account.
Build the tracking, tagging, and data infrastructure that makes cross-channel measurement reliable, and audit it regularly for gaps.
Own the metric dictionary: one documented definition for every metric we report, with its source, its owner, and its known caveats.
Define what measurement maturity looks like at each stage of a client relationship, and move every account up that ladder deliberately.
Set the standard for what good measurement looks like at Mass Culture, and hold every team accountable to it.
Own the standing narrative for each account: one continuous arc of what we believed, what we tested, what we learned, and what changed.
Hold every number we ship to one standard: what happened, why, what it means for the business, what we are doing about it, and what we need from the client.
State confidence explicitly. Separate signal from noise, and say plainly when a movement is not yet a result.
Name what would have to be true for a recommendation to be wrong, and what evidence would change our mind. We kill our own conclusions before a client has to.
Make findings survive translation. The same insight has to hold up for a channel specialist, an account strategist, and a founder or CFO, without quietly changing meaning on the way up.
Guard the line between narrative and spin. A good story that runs ahead of the evidence is a failure of this role, not a win.
Set and teach the house standard for how Mass Culture writes about data, and coach analysts and strategists to write to it.
Proactively turn raw performance data into clear, decision-ready insight: what's driving revenue and margin, what's not working, and what to test next.
Partner with Account Strategists and media channel leads to connect channel-level data to client business outcomes.
Lead the analytical narrative in QBRs and strategic reviews, presenting findings directly to senior client stakeholders.
Contribute measurement expertise to new business pitches and client onboarding.
Partner with strategy to design and run incrementality tests, holdout studies, geo experiments, and media mix experiments that validate, or kill, strategic assumptions.
Build and maintain a multi-year learning agenda per account: a testing roadmap tied to the business questions that actually matter, not a backlog of curiosities.
Own the experiment record. Every test carries a documented hypothesis, design, minimum detectable effect, result, and the decision it changed. Findings get applied, not filed away.
Champion radical transparency in reporting: when something isn't working, the data says so before the client has to ask.
Own creative measurement end to end, including creative attribution, fatigue, and testing frameworks, in partnership with Brains and our creative strategy team.
Make sure creative decisions are made on evidence, and that what we learn about creative travels across accounts instead of dying in one.
Co-own the measurement roadmap for the Mass Culture client portal with agency leadership: metric definitions, experiment tracking, attribution lenses, and how uncertainty gets represented to clients.
Build in the platform directly. You will author KPIs, widgets, and reporting views yourself rather than describing them to someone else.
Own the tools and platforms that power agency-wide reporting (the portal, GA4, Looker Studio, data warehouses, and similar), and make the build-versus-buy calls.
Manage and develop the analytics function, including the Agency Insights Lead and data analysts, setting clear standards for rigor and output quality.
Train account and channel teams on measurement fundamentals so good analytical thinking isn't confined to one department.
Evaluate and implement AI and automation tools that improve forecasting speed, pattern detection, and reporting efficiency.
Ensure automation strengthens analytical rigor rather than replacing it. We expect AI to make good analysts sharper, not to stand in for judgment.