Own the Customer Experience technology roadmap, improve the CX tool stack, and lead automation and AI-powered workflows while partnering with IT and Digital Product and developing a direct report.
Manager, Product Analytics
📜 Description
- Lead, coach, and grow a team of about 5 analysts embedded with Pricing, Supply, and Content.
- Partner with product and business leaders to shape roadmaps, challenge assumptions, and identify opportunities.
- Own experimentation, including test design, sample sizing, guardrail metrics, readouts, and causal methods when randomization is not feasible.
- Analyze pricing and marketplace dynamics, including elasticity, demand, conversion, supplier performance, margin tradeoffs, and customer segments.
- Evaluate and improve pricing models, and set standards for rigorous metrics, statistical reasoning, and actionable storytelling.
- Partner with data teams to strengthen data foundations and self-serve tools, and promote effective, verified use of AI tools.
🛠️ 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, including hiring and retaining talent.
- Experience designing, running, and interpreting A/B tests at scale; working knowledge of causal inference methods.
- Strong statistical foundations, including regression, hypothesis testing, and variance reduction; able to assess predictive or pricing models.
- Expert SQL skills and proficiency in Python or R for analysis and modeling.
- Product-first mindset, with examples of analysis that changed a roadmap, launch, or pricing decision and delivered measurable impact.
- Strong communication and stakeholder influence skills across technical and non-technical audiences.
- Preferred: experience with pricing, marketplaces, forecasting, B2B experimentation, analytics infrastructure, modern data tools, or high-transaction industries.
✨ Benefits
- Competitive base pay tied to role and experience
- Equity for all employees
- Some roles may include an annual bonus
Full job description
About Engine
Engine is the AI-native platform for intelligent travel. For a decade, Engine has built the proprietary technology and supply behind modern business travel, serving over 40,000 customers and nearly 2 million travelers, along with leading travel and AI companies that build on Engine's infrastructure. One system powers business travel, group travel, human agents, and AI agents.
That work has earned Engine recognition as TravelTech's Reservation Platform of the Year (2026), a spot on Inc.'s Power Partners list (2026), and one of Built In's Best Places to Work (2020–2026).
We're looking for bold, ambitious people to help redefine how businesses manage and experience travel. Working here, you can expect exponential growth, an ambitious pace, full ownership, and high-caliber colleagues who push you to do the best work of your career. Every hire raises the bar.
Come outpace the ordinary and build the future of travel with us.
We’re looking for an Analytics Manager to lead product analytics for our Pricing & Supply teams. This group powers Engine-only rates, our marketplace coverage and how competitive we are. Its decisions move conversion, margin and customer value every day.
This is a product-first leadership role. You and your team will sit inside product pods as thought partners who shape the roadmap, not as a reporting function waiting on tickets. Experimentation is how we make decisions here: you’ll set the standard for how Pricing & Supply tests, measures and learns. You’ll also take on technically demanding problems such as pricing models, demand and elasticity analysis, and causal questions that a simple A/B test can’t answer.
You don’t need a pricing or supply background. You do need to be excited by hard marketplace problems and by building a team that turns them into better products and better decisions. Join us in reshaping how businesses experience travel.
What You’ll Do
- 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.
Required
- 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.
Compensation
Our compensation packages are based on several factors, including your experience, expertise, and location. In addition to a competitive base salary, all roles receive equity. Depending on the role, total compensation may also include an annual bonus. Your recruiter will share your complete compensation package as you move through the process.
The Engine Edge: Perks & Compensation
We believe in rewarding great work with great benefits:
- Compensation: Competitive base pay tied to role and experience, with equity for all employees. Some roles are also eligible for bonuses or commissions.
- Benefits: Check out our full list at engine.com/culture
- Environments for Success: Different roles have different needs in terms of the environments that drive success which is why we have a hybrid-hub model. Whether you are in one of our amazing offices or fully remote, we'll make sure you have what you need to succeed.
Perks and benefits may vary based on employment type, location, and more
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