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Senior Product Analyst

Art of Problem Solving
CompanyArt of Problem Solving
CategoryProduct
LocationSan Diego
RemoteOn-site (inferred)
EmploymentNot stated
LevelSenior
SalaryNot stated by the employer
Posted27 Feb 2026
Last verified7 Aug 2026
SourceEmployer ATS (greenhouse)
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Description
At AoPS, data plays a critical role in how we design, build, and improve our products. We serve tens of thousands of students worldwide through digital platforms that support discovery, enrollment, learning, and ongoing engagement. These products generate rich behavioral and operational data, but that data only creates value when it drives better decisions. We are hiring a Senior Product Analyst to serve as a core strategic partner to the Product team. This is an individual contributor role for someone with deep expertise in product metrics, user behavior analysis, and experimentation. The role exists to sharpen our understanding of how users interact with our products, surface actionable insights, and ensure every product decision is grounded in evidence. The Senior Product Analyst is, above all, an advocate for our users. They use data to understand how students and families actually experience our products. You will work closely with product managers, engineers, and designers to define success, evaluate product changes, and help AoPS build experiences that deliver real value to students and families. The Senior Product Analyst will: Act as the primary analytics partner for the AoPS Product teams, supporting product strategy, roadmap decisions, and feature evaluation Proactively identify opportunities, risks, and trends in product data, surfacing insights without waiting for explicit requests Define, own, and evolve product metrics (including north-star metrics, leading indicators, and guardrail metrics), ensuring alignment and consistent interpretation across teams Translate product goals into clear measurement plans: testable hypotheses, success metrics, and tracking requirements Design, execute, and analyze A/B tests and other experiments (e.g., feature rollouts, holdout tests) to rigorously measure the impact of product changes and guide iteration Conduct deep-dive analyses of user behavior, funnels, retention, and engagement to uncover the "why" behind key product trends Build and maintain dashboards and self-service reporting that empower product managers and stakeholders to answer their own questions Partner with engineering to ensure reliable, well-instrumented event tracking across products Use SQL to extract, transform, and analyze large datasets from our data warehouse Communicate findings clearly, influencing product prioritization and direction through data-backed recommendations, reports, and presentations Establish and promote best practices for product analytics, experimentation, and metric integrity across the organization The ideal candidate has: 5+ years of experience in product analytics, growth analytics, or a related quantitative role, with demonstrated impact on product decisions Advanced SQL skills and experience querying large datasets from cloud data warehouses. We use Redshift Experience with Python (e.g., pandas, scipy, statsmodels) for data analysis and statistical work Deep familiarity with product analytics platforms and event-based data models. We use Mixpanel Proven ability to design, run, and interpret A/B tests, including a solid understanding of statistical significance, power analysis, and common experimentation pitfalls Experience defining and owning product metrics and building organizational alignment around them Strong ability to analyze user behavior (funnels, retention, segmentation, cohort analysis) and translate findings into clear product recommendations Proficiency building dashboards and self-service reporting tools. We use Lightdash Proven ability to operate as a strategic thought partner to the product and leadership teams, building trust and influence across engineering, design, and business stakeholders Excellent communication skills — able to translate complex analysis into clear, actionable guidance for both technical and non-technical audiences Comfort owning work end-to-end, from raw data through executive-