A deep dive into the methodologies, frameworks, and tools I use to build products that scale.
I map every touchpoint from first interaction to long-term retention. Understanding user behavior through data and empathy allows me to identify friction points and optimization opportunities.
From activation funnels to churn analysis, journey mapping informs product decisions at every stage.
I run lean, focused sprints with clear priorities and measurable outcomes. From backlog grooming to sprint reviews, I keep engineering teams aligned and shipping consistently.
Velocity tracking, capacity planning, and continuous retrospectives drive iterative improvement.
I manage products through every stage — from ideation and MVP launch through growth and maturity. Understanding where a product sits in its lifecycle shapes strategy.
Early stage means rapid experimentation. Growth demands scaling. Maturity requires optimization and lifecycle extension.
I've built and managed data pipelines that extract from 200+ sources, transform for analytics, and load into warehouses. Reverse ETL activates that data back into business tools.
Understanding data flow is critical for product decisions — from schema design to sync frequency to error handling.
SQL is my daily driver. From ad-hoc analysis to building complex analytics queries, I dig into data to find insights that drive product decisions.
Cohort analysis, funnel metrics, retention curves — I turn raw data into actionable intelligence.
I write clear, developer-friendly API documentation that reduces support burden and accelerates integration time. From endpoint specs to authentication flows.
Good docs are a product feature — they directly impact adoption and developer experience.
I work directly in Figma to create wireframes, annotate designs, and collaborate with design teams. Understanding design tools helps bridge the gap between product and design.
From low-fi concepts to detailed specs, I speak the language of design.
I define acceptance criteria, write test cases, and validate data quality before launch. A rigorous QA mindset ensures reliability and trust in the product.
From edge cases to regression testing, quality is non-negotiable.
I manage sprints, track velocity, and maintain a clean backlog in JIRA. Stories, bugs, and tasks are structured with clear acceptance criteria and estimates.
Good ticket hygiene keeps teams aligned and accountable.
I design and analyze experiments to validate hypotheses with data. From button copy to pricing tiers, testing removes guesswork from product decisions.
Statistical significance, sample sizes, and proper segmentation ensure reliable results.
I led the development of Ask Neo, a GenAI-powered data analyst that lets users query data in natural language. From prompt engineering to UX flows for AI interactions.
Building AI products requires balancing capability with reliability and trust.
I write clear, comprehensive PRDs that align stakeholders and guide engineering. Problem statements, success metrics, scope, and acceptance criteria — all documented.
A good PRD is a shared source of truth that reduces ambiguity and speeds up delivery.