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West Haven, Connecticut, United States
Remote only
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr. Product Analyst based in Brazil.
The Sr. Product Analyst will serve as a strategic analytics partner to product teams, helping shape product roadmaps, prioritize opportunities, and measure the impact of product decisions. This senior individual contributor role combines advanced data analysis, experimentation, and product measurement to improve digital experiences for both consumers and business partners. You will own key metrics across product funnels, feature adoption, engagement, and retention, translating complex behavioral data into actionable recommendations. Working closely with Product, Design, UX Research, and Data Engineering, you will design experiments, establish measurement standards, and ensure data quality throughout the product lifecycle. AI-powered analytics will be central to your daily work, using Claude, Claude Code, and automated workflows to accelerate insights and improve self-service analytics. This remote opportunity is ideal for an analytically rigorous, independent professional who can influence decisions, communicate confidently with leadership, and promote responsible, evidence-based use of data and AI.
Product strategy and insights
Partner directly with product teams during planning and roadmap discussions to identify, assess, and prioritize opportunities before development begins.
Define and maintain consistent metrics and measurement standards across dashboards and the semantic layer.
Own measurement of product funnels, feature adoption, engagement, and retention across consumer-facing and school-facing experiences.
Conduct in-depth analyses of user behavior and audience segments, pairing each finding with clear recommendations and actionable next steps.
Proactively identify friction points, user drop-offs, and improvement opportunities, collaborating with Product, Design, and UX Research to combine behavioral data with qualitative insights.
Experimentation and impact measurement
Lead A/B tests from design through analysis, including experiment sizing, guardrail metrics, duration, tracking setup, and interpretation of results.
Configure and validate experiment tracking through Google Tag Manager (GTM) and Google Analytics 4 (GA4).
Distinguish meaningful signals from statistical noise and communicate findings, limitations, and confidence levels clearly.
Contribute to experimentation standards and ensure tests are connected to meaningful business and product outcomes rather than superficial engagement metrics.
Measure launches that cannot be randomized using appropriate causal inference methods and clearly communicate the strength of the evidence.
Measurement implementation and data quality
Define measurement requirements and GA4 event specifications for new features before launch.
Build and test GTM tags and collaborate with Data Engineering on server-side tracking and data pipeline requirements.
Conduct post-launch data quality checks, review tracking changes made by partner teams, and identify issues related to consent, missing events, or incomplete tracking.
Build and maintain dashboards and self-service analytical tools, including Streamlit applications, to help product managers answer recurring questions independently.
Contribute to dbt models and the self-service semantic layer in partnership with Data Engineering.
Support new data systems and tracking changes, including consent management, reporting requirements, GA4 reconciliation, and launch measurement.
AI-powered analytics and automation
Use Claude and Claude Code daily to write and review SQL, explore datasets, draft analytical summaries, and build Streamlit applications.
Develop and maintain the semantic layer, Claude skills, and supporting context, including metric definitions, table guides, and experimentation standards, to improve the reliability of AI-assisted analytics.
Automate recurring analytical tasks such as experiment readouts, KPI monitoring, and launch reviews using AI-driven workflows.
Use AI tools to identify product launches that require measurement planning and help teams incorporate analytics into product development.
Enable product managers to use AI-assisted self-service analytics by maintaining approved skills and metric definitions, coaching stakeholders on interpreting data, and reviewing findings before they inform decisions.
Support the adoption of AI tools across Analytics and Product teams and help establish standards for validating AI-generated outputs.
Analytical rigor and stakeholder influence
Maintain high standards for reproducible SQL, documented analytical methods, validated results, and clear distinctions between correlation and causation.
Independently verify AI-generated queries, calculations, and reasoning before using or sharing analytical outputs.
Informally mentor analysts and review or challenge analyses produced by colleagues and product partners, including AI-assisted work.
Present findings and recommendations to product and company leadership, clearly explaining the business implications and recommended actions.
Over time, build a scalable measurement framework for assigned product areas, influence roadmap prioritization, and contribute improvements to the Analytics team's tools, methods, and processes.
Experience: At least 5 years of experience in product analytics, data analytics, or a closely related data-focused role.
Demonstrated experience designing, analyzing, and managing A/B tests, as well as owning product measurement from planning through post-launch evaluation.
Hands-on experience analyzing web or application behavioral data using GA4, GTM, PostHog, Amplitude, Mixpanel, or similar platforms, including an understanding of their limitations.
Practical experience using Claude, Claude Code, or comparable AI tools in analytics work, with examples of workflows or automations developed.
Proven ability to influence product decisions and roadmap priorities through data-driven insights.
Strong SQL proficiency, including independently writing, reviewing, optimizing, and debugging complex queries.
Solid knowledge of statistics and experimentation, with experience using Python or R for analytical work.
Experience with Snowflake, dbt, and version-controlled analytics workflows.
Strong dashboarding and data visualization skills using Streamlit, Looker, or comparable tools.
Proficiency with AI-assisted analytical workflows, including effective prompting, providing appropriate context, and carefully validating generated queries, calculations, and results.
Ability to work independently as a senior individual contributor, influence stakeholders without formal authority, and navigate ambiguous problems in a fast-paced, cross-functional environment.
Excellent communication skills, with the ability to translate complex analytical findings into clear, practical recommendations for non-technical audiences and leadership.
Bachelor's degree in Statistics, Data Science, Economics, Computer Science, or a related quantitative discipline, or equivalent practical experience. A Master's degree is a plus.
Nice to have: Experience building Claude skills, Model Context Protocol (MCP) connectors, or agent workflows for a team.
Nice to have: Familiarity with K–12 education or college admissions processes.
Nice to have: Experience with causal inference methods beyond A/B testing.
Nice to have: Experience contributing to a semantic layer or self-service metrics framework.
Nice to have: Background in marketplaces, consumer internet, Software as a Service (SaaS), or education technology.
Location eligibility: Applicants must be based in Brazil or Argentina. US-based candidates are not being considered for this position.
Application language: CVs and applications must be submitted in English.
Remote work: All interviews are conducted remotely, and the role is listed as remote.
Senior individual contributor opportunity: Work closely with product leadership and influence product strategy, measurement, and roadmap decisions.
AI-driven working environment: Use Claude, Claude Code, and AI-assisted workflows as core tools in everyday analytics work.
Cross-functional collaboration: Partner with Product, Design, UX Research, Data Engineering, and Analytics colleagues.
Professional development: Build expertise in experimentation, causal analysis, semantic layers, self-service analytics, and AI-powered automation.
Meaningful product impact: Help improve digital experiences by identifying user needs, evaluating product performance, and translating data into actionable decisions.
Structured onboarding and development milestones: The role includes defined expectations for the first month and the 3-, 6-, and 12-month milestones, covering stakeholder relationships, product analytics ownership, experimentation standards, and scalable measurement.
Candidate accessibility: Interview accommodations can be requested to help ensure a comfortable and positive interview experience.