Product Analyst | San Francisco on-site

Grid•San Francisco, CA

3d•Onsite

About The Position

Grid's mission is to level the playing field by building financial products that help users better manage their financial future. The Grid app lets users access cash, build credit, spend money, optimize their taxes, and lots, lots more. Grid is a fast-growing team that’s deeply passionate about making a difference in the lives of millions. We’re solving huge problems and believe that every team member has a big role to play. Come join our growing team in Seattle! The Role We’re looking for a sharp and data-driven Product Analyst to join our product team. In this role, you’ll work at the intersection of data, product strategy, and user insights to help Grid build better financial products. You’ll dig into user behavior, surface actionable insights, and partner closely with product managers and engineers to guide decisions that directly impact millions of users.

Requirements

Strong proficiency in SQL and comfort working with large datasets
Experience with modern data tooling (e.g., Looker, BigQuery, etc.)
Hands-on experience using AI tools (e.g., ChatGPT, Claude, Cursor, etc.) to: write and optimize queries automate workflows build internal tools or prototypes
Ability to build, not just analyze : scripting (Python preferred) building lightweight apps, tools, or automations
Solid understanding of experimentation and statistics (A/B testing, significance, causal inference)
Strong product intuition and ability to prioritize high-impact opportunities
Excellent communication skills with the ability to distill complex insights into clear recommendations
High agency and curiosity—someone who looks for ways to eliminate manual work and scale themselves with AI
Degree from a top-tier (Tier 1) university in a quantitative or technical field (e.g., CS, Math, Economics, Engineering)
Ability to work out of our San Francisco office
You must be legally authorized to work in the United States at the time of hire.

Responsibilities

Own end-to-end decision systems , not just analysis—design, build, and iterate on tools that drive product and growth decisions
Use AI (e.g., LLMs, copilots, automation workflows) to automate analysis, reporting, and insight generation
Build lightweight internal data products and tools (e.g., self-serve dashboards, GPT-powered interfaces, experimentation tools) that scale decision-making across the org
Partner with product, engineering, and growth to define success metrics and design experiments , while leveraging AI to accelerate test design and interpretation
Identify opportunities across the funnel (acquisition, activation, retention, monetization) and rapidly prototype solutions using data + AI
Translate complex datasets into clear, high-leverage recommendations , often via automated or semi-automated systems
Continuously improve data infrastructure, instrumentation, and workflows to enable faster, higher-quality decisions
Develop a deep understanding of our users and their financial behavior, and encode that understanding into scalable models and tools