Product Analyst

We're looking for a rigorous, product-minded analyst who lives at the intersection of data and decision-making. In this role, you'll own product health tracking, user behaviour analysis, and insight delivery across GobbleCube's core platform. You won't just report numbers: you'll shape how the product team understands what's working, what's not, and where to invest next. This is a high-leverage role for someone who can move seamlessly between exploratory analysis and structured storytelling, and who takes personal ownership of the quality and timeliness of the insights they deliver.

Responsibilities:

• Own the product analytics stack: define, build, and maintain dashboards and metric frameworks that track feature adoption, engagement, retention, and revenue impact across the platform.
• Partner with PMs, Customer Success, and Data Science teams to design instrumentation, run experiment analyses, and translate findings into product decisions.
• Drive weekly and monthly product health reviews: surface anomalies, run root cause analyses (RCA), and proactively flag risks before they become escalations.
• Build a deep understanding of the product lifecycle: from discovery to launch to iteration, and maintain longitudinal tracking that connects feature releases to downstream user behaviour.
• Develop and maintain a user behaviour taxonomy: funnels, cohort analyses, segmentation by persona, platform, and usage tier.
• Translate complex analytical outputs into clear, concise narratives for product leadership and GTM audiences.
• Identify instrumentation gaps, work with engineering to close them, and establish a culture of measurement rigour within the product org.

Requirements:

• 2+ years of hands-on product analytics experience in a B2B SaaS or consumer tech environment: not just data analysis, but analytics that directly informed product roadmap or business decisions.
• Strong command of SQL (complex joins, window functions, CTEs) and Python (pandas, NumPy) for data wrangling and exploratory analysis.
• Proficiency with product analytics and BI tools: Mixpanel, Amplitude, PostHog, Metabase, Redash, or equivalent.
• Demonstrated experience tracking products through their lifecycle: instrumentation design, launch metrics, post-launch iteration, and long-term health monitoring.
• Ability to define and operationalise product KPIs: you should be able to articulate the difference between a vanity metric and a signal that drives decisions.
• Experience with A/B testing and experimentation frameworks: hypothesis design, statistical significance, and communicating results to non-technical stakeholders.
• Exceptional structured thinking: you can decompose a fuzzy product question into a precise analytical plan and execute it end-to-end.
• Strong communication skills: you can write a crisp insight brief as well as you can build a dashboard.
• Practical fluency with AI tools and workflows: you actively use LLMs (Claude, ChatGPT, or equivalent) in your day-to-day work for analysis, synthesis, and automation, not just experimentation.
• Familiarity with agentic workflows and automation tooling: experience connecting data sources, triggers, and actions using tools like Claude, MCP integrations, Zapier, or custom Python pipelines.

Nice to Have:

• Prior experience in quick commerce, FMCG analytics, or marketplace platforms.
• Exposure to event-based data pipelines and warehouse tooling (BigQuery, Snowflake, dbt).