Product Data Analyst

Job not on LinkedIn

🕒 June 3

🌐 United States, Canada – Remote

🇺🇸 United States – Remote 🇨🇦 Canada – Remote

🗽 New York – Remote

🗽 New York – Remote

💵 $145k - $175k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

📉 Data Analyst

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Wand

WebsiteLinkedInAll Job Openings

1 - 10 employees

💼 Consulting

📣 Marketing

🤖 Artificial Intelligence

Consulting • Marketing • Artificial Intelligence

Wand is a mobile-first AI-powered drawing and illustration app designed for iPhone and iPad that lets artists sketch, render, edit, recolor, and apply styles in seconds using on-device and private models. Built by artists for artists, Wand offers multi-layer support, a custom brush engine, preloaded style libraries, dataset storage, and features like regional iterative editing, transparent PNG export, and Apple Pencil optimization to streamline creative workflows. It emphasizes privacy for custom models, collaboration and learning tools for students and professionals, and desktop browser support for color editing.

📋 Description

• You'll own the metrics that run the business. • You'll own the dashboards and definitions Product, Growth, Marketing, and Finance rely on every day. • You'll build in Hex, document in our spec, and enforce consistent definitions across teams. • When retention dips or a funnel leaks, you won't stop at the symptom. • You'll follow the thread — through cohorts, segments, the quirks of specific games — until you can name the cause and recommend a fix. • You'll design and analyze A/B tests on product changes, pricing, onboarding, and growth initiatives. • You'll set sample sizes, call stat sig, and write the readouts. • You'll work directly with our leaders on the questions that don't have obvious answers. • You'll frame the question, run the analysis, and deliver the recommendation.

🎯 Requirements

• 5 years in a Data Analyst, Product Analyst, or Business Intelligence role (excluding internships) • SQL fluency — complex joins, incremental computation, window functions, query optimization; comfortable with large, messy datasets • Python for analysis — pandas and statistical libraries; you don't freeze when the answer requires code • Experimentation chops — hypothesis testing, sample sizing, and the judgment to tell a p-value from an insight • A track record of moving metrics you cared about (we'll ask you to walk us through one) • Direct communication — you can tell a leader an uncomfortable answer without burying it in caveats. • Degree in a quantitative field • Hex, dbt, and Bigquery experience • Prior growth-stage consumer software or gaming experience • Causal inference methods (diff-in-diff, regression discontinuity, propensity matching) • Prior work on LTV, retention, or subscription models • Experience building metrics frameworks or KPI hierarchies from scratch