JD Case Study · Chime

Director, Product Analytics

A Director owning product analytics at a leading neobank — member engagement metrics, the experimentation program, and the evidence behind product decisions. The growth-analytics engine I built (funnel, LTV, experimentation, scorecard) is exactly this, and I’ve already mapped Chime’s competitive lane in a spotlight.

San Francisco · hybrid · $221K–$282K · View the job description →

Jun 22, 2026

What they’re actually buying

Be the analytical conscience of the product org. Define the member-engagement metrics, run a rigorous experimentation program, and turn member behavior into the prioritization calls product actually makes. The job is measuring what truly moves activation, engagement, and retention — and being willing to say so with evidence when the answer is inconvenient.

How I’d own it — first 90 days

Days 1–30

Map the member lifecycle

Baseline the funnel — signup → activated (direct deposit) → engaged → retained — and the north-star. Meet Product, Growth, and Data, and find the engagement steps that predict long-term retention.

Days 31–60

Level up experimentation

Audit the test program, standardize readouts (confidence intervals, guardrails, sample-size), and ship a member-engagement scorecard that actually drives roadmap prioritization — not a metrics wall.

Days 61–90

Land an incrementality win

Run and measure a high-leverage experiment (likely direct-deposit activation), deliver the readout with its roadmap implication, and lock in the test-and-learn governance the org runs by.

Signature analysis: the neobank member lifecycle

Signups 100 indexed to 100

Activated (direct deposit) 47

Engaged (weekly active) 38

Retained at 12 months 31 the base that monetizes

The retention unlock: direct-deposit activation. Members who set up DD retain dramatically longer and drive the interchange that funds the model. An A/B on the activation flow that lifts DD setup a few points compounds through every later stage — so that’s the experiment I’d prioritize first.

Illustrative figures to demonstrate the lens — a member lifecycle funnel with the highest-leverage activation step identified for experimentation.

Requirement → proof

What the JD asks for	What I’ve already shipped
Product / lifecycle analytics, engagement metrics	A full member-style lifecycle funnel + engagement scorecard, calibrated to real results.
Experimentation & causal inference	An A/B + incrementality readout with CIs, guardrails, and a sample-size calculator.
Executive scorecards — insight, not metrics	A growth scorecard built to surface actions and the next experiment.
SQL / Python, modern warehouse	Show-the-SQL blocks (cohort LTV, funnel by channel), warehouse-ready.
Neobank / cash-advance domain	A competitor spotlight on Dave — Chime’s direct neighbor in cash advance and member growth.

The same engine

The engine is the same one this portfolio runs on — acquisition→retention funnel, LTV, experimentation, an exec scorecard — and I’ve already studied Chime’s lane closely enough to publish on it. I’d spend week one running experiments, not learning what a member funnel is.

Read my Dave spotlight →

Hire the work, not the headcount

You’ve already priced this role. Here’s what the money buys.

Chime says Director, Product Analytics is worth $221K–$282K a year (posted base range). Fully loaded — payroll taxes, health insurance, benefits, roughly +25% — the midpoint runs about $315K a year: $151 an hour, for all 2,080 hours, ramp and meetings included. And the ramp is real: a new leader’s breakeven averages about 6 months (Watkins, The First 90 Days) — call it $158K spent before the first shipped thing. The candidate who interviews well will be great in the room and diligent on the kanban board. What they won’t do is build the systems. That’s the part I sell.

The build · 90 days

$30,000

~120 hours ships the first-year plan on this page as working systems on your data — dashboards, pipelines, automations that keep running after I stop billing. Value in week one, not month 9. Compare: $158K for the hire’s ramp alone.

The rate

$250/hr

Yes — 1.7× your hire’s loaded hourly. But you buy the ~120 hours that ship, not the 2,080 that mostly don’t. Priced per outcome instead of per hour, it isn’t close.

The bench · after the build

$3,500/mo

My agents run your refreshes and monitors on a schedule — the same fleet that keeps this site’s data current — and I stay on call. Month to month; cancel anytime; the systems are yours either way.

Founding-build rate: the first 3 builds run $15,000 — half the list price — in exchange for a named, written case study. When the third case study ships, so does this rate.

Or keep the req. Hire the person who’s great in the room — and pay me to make them dangerous: the same $30,000 build, handed to your new director on day one, pulls their breakeven from month 6+ to month two. The expensive mistake isn’t the hire; it’s the hire with no system underneath them. This case study is the free sample of what the system looks like.

Email me the req All services & prices

Product analytics is the discipline I’ve shipped end-to-end, in public, in your exact lane. Let’s talk about what’s moving your member retention. — Paul Brown