Principal Product Data Scientist

Overview

As a Principal Product Data Scientist, you lead the data science vision for Product, shaping tooling, platforms, and AI-driven capabilities that power better customer experiences. You’ll influence senior leaders and cross-functional partners, driving scalable, automated analytics and high-impact use cases from proof of concept to production. You help the company embed data-driven decision making at the highest levels and scale data science capabilities across the organization. This role offers strategic influence, technical leadership, and opportunities to shape travel tech products at scale.

Responsibilities

• Define and lead the Data Science strategy for Product to embed analytics and AI in product development
• Advise senior Product and Engineering leadership on data-driven decisions
• Develop and promote next-gen data science tooling, automation, and scalable platforms
• Explore and operationalize emerging AI technologies and high-impact use cases from POC to production
• Advance experimentation, causal inference, and uplift modeling to ensure rigorous decision-making
• Tackle complex analytical projects and translate questions into actionable product recommendations
• Mentor and develop other Data Scientists and Analysts
• Scale impact through automation, self-service, and democratization of data science
• Develop customer segmentation and predictive models to guide the product roadmap
• Communicate complex technical concepts to cross-functional teams across Product, Engineering, Design, and Commercial

Key requirements

• Extensive experience in data science or a similar quantitative role with influence on product organization
• Expert-level proficiency in Python and SQL
• Hands-on experience with statistical modeling, quasi-experimentation, multi-armed bandits, and ML techniques (regression, classification, clustering)
• Ability to define, implement, and operationalize product metrics from scratch
• Proven track record driving strategic impact and leading technical discussions with cross-functional partners
• Experience scaling analytics capabilities and building automated/self-service data products
• Strong critical thinking and leadership in mentoring teams
• Excellent collaboration and communication skills across levels

• Strategic influence
• Mentoring and leadership
• Cross-functional collaboration
• Python
• SQL
• Statistical modeling

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