Manager, Product Analytics

Engine is hiring a Manager, Product Analytics to lead product analytics for its Pricing & Supply teams. The role leads an embedded analyst team, shapes product roadmaps, owns experimentation, and guides analysis of pricing, marketplace dynamics, and models that inform business decisions.

Responsibilities:

• Lead, coach and grow a team of about 5 analysts embedded with Pricing, Supply and Content
• Act as a strategic partner to product and business leaders. Shape roadmaps, challenge assumptions and bring forward opportunities nobody asked you to find
• Own the experimentation program for Pricing & Supply: test design, power and sample sizing, guardrail metrics, readouts, and the judgment to know when not to test
• Go beyond basic A/B testing when the problem needs it. Use holdouts, quasi-experiments, difference-in-differences, or matching when randomization isn’t possible or two-week tests miss the real effect
• Lead analysis on pricing and marketplace dynamics, including price elasticity, demand and conversion modeling, rate competitiveness, supplier performance, margin tradeoffs and customer segmentation
• Partner with Pricing to evaluate, stress-test and improve the models that drive Engine-only rates. Make sure the team understands what drives model outputs, not just what the outputs are
• Set a high bar for rigor: clear metric definitions, sound statistics, honest uncertainty, and storytelling that leads to action
• Push back with evidence when a decision, launch or metric doesn’t hold up, and coach your team to do the same
• Work with Data Engineering and Analytics Engineering to strengthen data foundations, canonical metrics and self-serve tools, so your team spends its time on high-leverage work
• Model an AI-forward way of working and build team habits for using AI tools well, including verifying what they produce

Requirements:

• 7+ years in product analytics, product data science, or a closely related role, embedded with product and engineering teams
• 3+ years managing and developing analysts or data scientists, with a track record of hiring and retaining strong talent
• Deep experimentation experience: designing, running and interpreting A/B tests at scale, plus a working knowledge of causal inference methods for cases where clean randomization isn't available
• Strong statistical foundations, including regression, hypothesis testing, and variance reduction or similar techniques
• Comfortable working with and pressure-testing predictive or pricing models
• Expert SQL on large, complex datasets, and proficiency in Python or R for analysis and modeling
• A product-first mindset: you start with the customer, the business and the decision at hand, not the warehouse
• Clear examples of insights you or your team started that changed a roadmap, launch or pricing decision, with measurable impact
• The conviction to hold a well-reasoned position with senior stakeholders, and the communication skills to influence technical and non-technical audiences alike
• Experience with pricing, revenue management, marketplaces, supply or inventory, or other two-sided businesses
• Experience with demand forecasting, price elasticity, or optimization problems
• B2B experimentation experience, such as account-level randomization, small samples, or multi-user accounts
• Experience building an analytics or experimentation function from an early stage: telemetry, canonical metrics, testing infrastructure
• Familiarity with modern data tools such as Snowflake, dbt, Looker, Hex, or experimentation platforms
• Experience in travel, hospitality, fintech, or other high-transaction businesses