Product Analyst

About This Role

This Product Analyst role is embedded within a product squad, providing analytical support to grow the company's two key marketplace platforms: the customer-facing platform and the partner-facing platform. The position involves deep analysis of user behavior, end-to-end analytics, and the planning and analysis of A/B tests. You will work in close collaboration with Product Managers to drive data-driven decisions, with a key focus on optimizing pricing strategies and identifying product growth opportunities.

Responsibilities

• Partner with Product Managers and stakeholders to define the problem, success metrics, and hypotheses; propose experiments and measure impact on the business
• Own product A/B testing and the end-to-end product hypothesis pipeline, from ideation to analysis and implementation
• Formulate hypotheses for new product features, design A/B experiments, analyze results, and provide recommendations to improve user conversion and engagement
• Design and analyze A/B tests for different pricing models and strategies to maximize revenue while balancing conversion rate and bookings
• Build and maintain dashboards in Looker; ensure correctness of data, clarity, usability, and decision support
• Analyze product funnels, user behavior, and platform performance (activation, conversion, retention, pricing effects) to drive product growth, revenue, and margin
• Track lifecycle KPIs, trends, and customer feedback, and recommend actions
• Conduct in-depth product analysis and uncover insights not covered by self-service analytics
• Specify data needs, validate data quality, and collaborate with DWH on marts and metrics
• Treat analytics as a product: start with “why,” simplify, and ensure usability and adoption

Requirements

• Education: Bachelor’s or Master’s in Data Science, Computer Science, IT, Engineering, or a related field
• Experience: 3+ years in product analytics, ideally within B2B/B2C marketplaces
• Technical Skills: Strong SQL and Python; experience with BI tools (Looker, Tableau, Qlik, or similar); familiarity with Git, JIRA, Confluence, or equivalents
• Quantitative Skills: Solid foundations in probability and statistics; hands-on experience with statistical analysis and experimentation (hypothesis testing, A/B test design, power analysis), regression, and time-series analysis
• Soft Skills: Strong business sense, clear communication, structured thinking, attention to data quality, and the ability to decompose ambiguous asks into deliverables
• Curiosity: A track record of self-directed development in adjacent disciplines such as entrepreneurship, business administration, product, UX, machine learning, or human behavior and psychology is a strong plus
• Languages: Fluent English with strong communication skills is required