Sr. Product Analyst (Brazil & Argentina ONLY)

About Niche Niche is the leader in school search. Our mission is to make researching and enrolling in schools easy, transparent, and free. With in-depth profiles on every school and college in America, 140 million reviews and ratings, and powerful search tools, we help millions of people find the right school for them. We also help thousands of schools recruit more best-fit students, by highlighting what makes them great and making it easier to visit and apply. Niche is all about finding where you belong, and that mission inspires how we operate every day. We want Niche to be a place where people truly enjoy working and can thrive professionally. About The Role **We are currently recruiting for this role in Argentina and Brazil only. We will not be considering US based candidates at this time. All interviews are being held remotely. If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.** **Only applications/resumes written in English will be accepted.** Niche’s product teams make dozens of decisions each quarter about what to build. We are looking for an analytically rigorous, product-minded Senior Product Analyst to help Niche decide what to build and know whether it worked. This is a senior individual contributor role on the Analytics team, embedded with our product teams and reporting to the Director of Product Analytics. You will own how we measure key product areas across our family-facing and school-facing experiences, such as rankings, scholarships, registration, and new products. You will be a strategic partner to product leadership, not a request queue. That means shaping questions before work starts, running the experiments that answer them, and staying with the work through the decision. Our analytics team works Claude-first: you will use Claude and Claude Code every day and help shape how the team and its partners use them. What You Will Do Product Strategy & Insight Embed with product teams as their analytics partner. Join planning and roadmap conversations and help identify and size opportunities before work is prioritized Define the metrics that matter for each product area and keep definitions consistent across dashboards and the semantic layer Own the measurement of product funnels, feature adoption, engagement, and retention for both families and school partners Run deep-dive analyses on user behavior and segments, and pair every finding with a recommendation and a clear next step Identify where users struggle or drop off and bring those opportunities to product managers proactively. Partner with Design and UX Research to pair behavioral data with qualitative insight Experimentation Own A/B tests with product teams end to end: design and sizing based on product requirements, guardrails and duration, tracking setup in GTM and GA4, and interpreting results with honest calls on signal versus noise Contribute to experimentation standards and apply them across your teams so tests are tied to business outcomes, not just clicks Measure launches that can’t be randomized, using appropriate causal methods and clear statements of confidence Measurement Partnership Write clear measurement requirements and GA4 event specs for new features before launch, build and test the GTM tags, and partner with Data Engineering on server-side and pipeline needs QA product data after launch, review GTM changes from partner teams, account for consent and tracking gaps, and flag quality issues early Build and maintain the dashboards and self-serve views (Streamlit) that let product managers answer their own recurring questions. Contribute to dbt models and the self-serve semantic layer with Data Engineering Support new data systems and tracking changes, such as consent management, with reporting requirements, GA4 reconciliation, and launch measurement Claude-Powered Analytics Use Claude and Claude Code as core daily tools: writing and reviewing SQL, exploring data, drafting readouts, and building Streamlit apps Build and maintain the semantic layer, Claude skills, and context (metric definitions, table guides, experiment standards) that make Claude reliable on Niche’s data Automate recurring work, such as test readouts, KPI monitoring, and launch reviews, with Claude-driven workflows Keep pace with AI-assisted product development by using Claude to spot launches that need measurement Help product managers self-serve with Claude: maintain the skills and sanctioned definitions they rely on, coach them on reading data, and review findings before they drive decisions Help analysts and product partners adopt Claude, and help define the team’s standards for validating its output Analytical Rigor & Influence Model rigor in product data: reproducible SQL, documented methods, validated results, and a clear line between correlation and causation Hold AI-assisted work to the same bar as your own: check the queries, numbers, and logic before anything ships Mentor analysts informally, and review and pressure-test analyses from the team and from product partners, including AI-assisted work Present findings to product and company leadership with a clear “so what” During the First Month: Meet stakeholders across Product, Analytics, and Data Engineering to learn team goals, roadmaps, and workflows Get set up with Claude, Claude Code, and the team’s existing skills. Learn our stack (Snowflake, dbt, Streamlit, GA4 data) and how product events are defined and captured Review existing product dashboards and reports to build a baseline view of core product KPIs Within 3 Months: Act as analytics partner to your assigned product teams, including defining metrics and reading out launches and tests Write measurement requirements for upcoming launches with Data Engineering Learn the boundaries and collaborations between Product Analytics and Data Engineering so ownership of shared data is clear Within 6 Months: Apply and help evolve experimentation standards across your teams Become the go-to expert on product behavior data, presenting findings and recommendations to cross-functional teams Ship at least one self-directed deep dive that influences a product decision, and build or improve one Claude skill or workflow the team reuses Within 12 Months: Use deep product and user knowledge to inform roadmap prioritization Build a scalable measurement framework for your product areas that helps teams make data-informed decisions on their own Contribute to the Analytics roadmap with new methods, tools, or process improvements What We Are Looking For Experience 5+ years in product analytics, data analytics, or a closely related data role Demonstrated experience designing and analyzing A/B tests and owning product measurement end to end Hands-on experience analyzing web or app behavioral data (GA4, GTM, PostHog, Amplitude, Mixpanel, or similar), including its limitations Hands-on experience using Claude, Claude Code, or similar AI tools in analytics work, with examples of workflows you built or automated Track record of influencing product decisions and roadmaps with data Proven ability to turn complex findings into clear recommendations for non-technical partners, and to say plainly when the data won’t support the question Experience in a fast-paced, cross-functional environment with shifting priorities Skills Senior SQL proficiency; comfortable writing, reviewing, and debugging complex queries independently Strong grounding in statistics and experimentation, with Python or R for analysis Experience with Snowflake, dbt, and version-controlled analytics work Strong dashboarding skills in Streamlit, Looker, or similar Fluency with Claude or similar AI tools: prompting well, giving models the right context, and checking every query and number they produce Comfort operating as a senior IC: influencing without authority and working self-directed on ambiguous problems Education Bachelor’s degree in Statistics, Data Science, Economics, Computer Science, or a related quantitative field, or equivalent practical experience. A Master’s degree is a plus Nice to Have Experience building Claude skills, MCP connectors, or agent workflows for a team Understanding of K-12 or college admissions processes Experience with causal inference methods beyond A/B tests Experience contributing to a semantic layer or self-serve metrics layer Background in marketplace, consumer internet, SaaS, or education technology Interview Process Candidate experience is a top priority for our talent and hiring teams. We believe in providing a transparent, authentic and comprehensive interview process where you have the opportunity to learn about us while we get to know you and your experience. The interview process is outlined here: Video Interview with Talent Acquisition Partner