Role Description
As a Product Analytics Engineer at Nous Research, you'll own the measurement systems that help us understand how users interact with Hermes Agent. You'll build the analytics foundation across our products—from instrumentation and event pipelines to dashboards and experimentation—then use that data to identify opportunities to improve activation, engagement, retention, and long-term product success.
You'll partner closely with Product, Engineering, Design, Support, and Leadership to turn behavioral insights into concrete product improvements. This role is ideal for someone who enjoys building reliable analytics infrastructure while also using data to influence product strategy and execution.
Responsibilities
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Own product analytics end-to-end, from event design and instrumentation through data modeling, analysis, and product recommendations.
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Define and maintain a consistent event taxonomy and shared metrics layer across Hermes Agent and Nous Portal.
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Implement and maintain analytics instrumentation across desktop, mobile, web, CLI, backend services, and third-party integrations.
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Build reliable data pipelines, transformations, dashboards, and monitoring systems that make product behavior easy to understand and trust.
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Analyze user funnels, cohorts, retention, behavioral paths, and churn to identify friction points and opportunities for improvement.
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Segment user behavior across platforms, acquisition channels, pricing plans, models, tools, and use cases to uncover actionable insights.
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Design and evaluate experiments, measuring the impact of product changes on activation, engagement, retention, conversion, and revenue.
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Partner with Product, Engineering, Design, and Support to translate data into prioritized product improvements.
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Combine quantitative analysis with qualitative feedback from users, customer conversations, and direct product usage to develop a complete understanding of user behavior.
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Build monitoring and alerting systems for key product metrics and proactively investigate anomalies.
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Establish best practices for analytics instrumentation, documentation, data quality, and privacy-conscious telemetry.
Qualifications
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5+ years of experience in Product Analytics, Analytics Engineering, Data Engineering, or a similarly technical product role.
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Expert SQL skills and strong proficiency in Python, with experience working in production application codebases using TypeScript, JavaScript, or similar languages.
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Hands-on experience implementing analytics instrumentation across client applications and backend systems.
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Experience with modern product analytics platforms such as PostHog, Amplitude, or Mixpanel, along with data warehouses and BI tools.
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Deep understanding of product metrics including activation, engagement, retention, churn, experimentation, and funnel analysis.
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Strong analytical and problem-solving skills with the ability to trace issues from dashboards through underlying systems and instrumentation.
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Excellent communication skills and the ability to translate complex behavioral data into clear product recommendations.
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Entrepreneurial mindset, strong ownership, and the ability to operate effectively in a fast-moving environment.
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Extensive use of AI-assisted development and analysis to improve speed, depth, and quality of work.
Nice-to-Have
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Experience working on AI products, LLM applications, AI agents, or developer tools.
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Familiarity with agent workflows, tool calling, model routing, memory systems, and other modern AI application patterns.
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Experience measuring cross-platform products spanning desktop, mobile, web, CLI, and enterprise deployments.
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Experience with subscription or usage-based SaaS products, including conversion, credits, renewals, and monetization.
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Experience designing privacy-conscious telemetry and analytics systems for open-source or developer-focused products.
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Experience building analytics systems that support high-volume event streams and rapidly growing products.
