Description:

Senior Product Analyst

Experience: 4 - 6 Years

Industry: Product Technology / E-commerce / SaaS

Role Summary:

We are seeking a high-caliber Senior Product Analyst to drive data-informed decision-making across our product ecosystem. In this role, you will act as a "Product Intelligence Lead," responsible for transforming raw data into strategic insights through advanced SQL mastery, sophisticated A/B testing, and automated data pipelines. You will bridge the gap between user behavior and business growth by designing rigorous experiments and building complex, self-service Tableau dashboards. The ideal candidate is a critical thinker who can simplify high-dimensional problems, perform deep-dive root-cause analyses, and communicate technical findings to stakeholders with clarity and impact.

Responsibilities:

- Advanced Data Extraction & Synthesis: Utilize mastery-level SQL to query massive datasets, performing complex joins and window functions to extract granular product insights.

- Product Experimentation (A/B Testing): Lead the end-to-end experimentation lifecycle, from power analysis and hypothesis generation to interpreting statistical significance and primary/secondary metric impact.

- Python-Driven Analysis: Leverage Python (Pandas, NumPy) for advanced statistical modeling, data cleaning, and automating repetitive analytical tasks.

- Self-Service Analytics Architecture: Design and maintain complex Tableau dashboards and underlying data pipelines that empower product managers to perform independent data discovery.

- Root-Cause & Deep-Dive Analysis: Structure and simplify complex business questions, leveraging data to perform root-cause analysis on fluctuating product KPIs.

- Metrics Definition & Governance: Define and track North Star metrics, ensuring data accuracy and consistency across all product reporting layers.

- Stakeholder Storytelling: Translate high-dimensional data and experiment results into actionable business recommendations for non-technical leadership in fluent English.

- Cross-Functional Collaboration: Partner closely with Product, Engineering, and Design teams to influence product roadmaps through data-backed evidence.

- Data Pipeline Optimization: Collaborate with Data Engineering to optimize data schemas and pipelines for faster, more reliable reporting.

Technical Requirements:

- SQL Mastery: Expert-level proficiency in writing highly optimized SQL for large-scale data analysis.

- Statistical Rigor: Hands-on experience with experimentation concepts, including power analysis, p-values, and confidence intervals in a product setting.

- Visualization Expertise: Proven ability to build complex, automated dashboards in Tableau.

- Programming: Strong proficiency in Python for data manipulation and statistical analysis.

- Analytical Thinking: Strong ability to structure ambiguous problems and leverage data for solution-building.

Preferred Skills:

- Advanced Statistics: Knowledge of Bayesian experimentation or Causal Inference is a significant plus.

- Product Tooling: Familiarity with event-tracking tools like Amplitude, Mixpanel, or Google Analytics 4.

- ETL Knowledge: Experience with dbt (data build tool) or Airflow for managing data transformation layers.

Core Competencies:

- Critical Problem Solving: Excellence in deconstructing "the why" behind user behavior changes.

- Communication Excellence: High fluency in English with the ability to present complex data stories effectively.

- Result Driven: A focus on moving beyond reporting to drive tangible improvements in product KPIs.

- Collaborative Spirit: A proactive approach to working within talented, multi-disciplinary squads.