Product Data Analyst

Vaga não está no LinkedIn

🕒 2 dias atrás

🗽 New York – Remoto

🗽 New York – Remote

💵 $145.000 - $175.000 / ano

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

📉 Analista de Dados

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Wand

SiteLinkedInTodas as Vagas

1 - 10 funcionários

🤖 Inteligência Artificial

👥 B2C

☁️ SaaS

Artificial Intelligence • B2C • SaaS

Wand é um aplicativo de desenho e ilustração com tecnologia de IA, desenvolvido para iPhone e iPad, que permite aos artistas esboçar, renderizar, editar, recolorir e aplicar estilos em segundos, utilizando modelos privados e no próprio dispositivo. Criado por artistas para artistas, o Wand oferece suporte a múltiplas camadas, um motor de pincel personalizado, bibliotecas de estilos pré-carregadas, armazenamento de conjuntos de dados e recursos como edição iterativa regional, exportação em PNG transparente e otimização para o Apple Pencil, visando otimizar os fluxos de trabalho criativos. Destaca-se pela privacidade para modelos personalizados, ferramentas de colaboração e aprendizagem para estudantes e profissionais, e suporte a navegador de desktop para edição de cores.

Descrição

• 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.

🎯 Requisitos

• 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