Senior Product Data Analyst
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Job Description
Senior Product Data Analyst at Introhive, an AI-powered relationship intelligence platform. Analyzing data to derive insights and improve product outcomes within the product operations team.
Responsibilities:
- Analyze user behaviour and outcomes to drive decisions
- Run funnel, cohort, retention, time-to-value, and feature adoption analyses; pinpoint drop-offs and root causes.
- Segment analytics by persona, account tier, industry, and/or region to illuminate who succeeds (or struggles) and why.
- Combine quantitative signals with VoC (Voice of the Customer) data to produce decision-ready recommendations with expected impact.
- Own product analytics platform & metrics framework
- Administer and evolve Pendo: event taxonomy, instrumentation to close gaps, governance, and data quality.
- Define standards for key product metrics at the product/feature level.
- Build and maintain dashboards for product health and usage, ensuring quality and self-serve capabilities.
- Drive VoC & GTM feedback loop data strategy
- Automate ingestion of product insights, unifying inputs from GTM, support, surveys, and call transcripts.
- Implement simple data pipelines to manage data in a robust, repeatable way, ensuring clear lineage and high data quality.
- Implement taxonomy and process for feedback to be efficiently categorized, summarized, and prioritized in a data-driven manner.
- Implement AI workflows (e.g., topic/intent extraction, clustering, summarization, anomaly detection) where feasible, with human-in-the-loop review and appropriate compliance guardrails.
- Contribute to the product commercialization process by helping to define and measure product outcome metrics for product investments to test hypotheses early-on, then to assess ROI on Beta/GA launches.
- Provide portfolio-level recommendations—what to scale, fix, or stop—based on impact and confidence.
- Conduct analysis to identify opportunities and validate direction for both near-term product improvements and larger strategic bets.
- Deliver self-serve dashboards, and/or training to raise analytics fluency; and help GTM team members use analytics as part of renewal and expansion motions.
- Collaborate with product managers to design hypothesis-driven experiments to increase activation, stickiness, and expansion; define success and guardrail metrics, do analysis, and make recommendations.
- Collaborate with product managers to identify and test growth levers with measurable outcomes.
Requirements:
- 5+ years of experience in data analysis, product operations, or adjacent roles
- Bachelor's degree in Computer Science, Engineering, Statistics, Business, or a related field
- Expertise in product analytics (funnel, cohort, retention, segmentation), experimentation, and causal thinking.
- Proficient with SQL, a BI tool (e.g., Tableau/Looker/Power BI), cloud data warehouses (e.g., Snowflake), and at least one product analytics platform (e.g., Amplitude/Mixpanel/Pendo) or equivalent.
- Skilled at using LLMs and AI tools to accelerate analysis and operations (e.g., generating SQL/code safely, summarizing usage/VoC, clustering themes, triaging feedback, and narrating dashboards).
- Comfortable combining quantitative signals with qualitative research to tell a cohesive story.
- Exceptional at building decision-ready narratives—clear visuals, plain language, and crisp recommendations.
- Experience defining event schemas, tagging strategies, and ensuring data quality at scale.
- Strong communication and stakeholder management; able to align PM, Engineering, UX, CS, and GTM around metrics and insights.
- Familiar with hypothesis design, guardrail metrics, and statistical concepts (e.g., confidence intervals, p-values, power).
- Pragmatic, organized, and with demonstrated experience managing multiple parallel initiatives and prioritizing effectively.
Benefits:
- Flexible work arrangements
- Professional development opportunities
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