Staff Data Scientist, Search & Personalization

Engine

105d • $210,000 - $245,000

About The Position

At Engine, we’re revolutionizing work travel. Our modern travel platform isn’t just about booking trips; it’s about transforming how businesses and their teams experience travel. From seamless booking options with top airlines, hotels, and car rental providers to single-invoice billing and flexible trip modifications, we make travel not only easier to manage but also enjoyable. Backed by powerhouse investors like Telescope Partners, Blackstone, Elefund, and Permira, we’re growing fast—and we want you to be part of it. As a founding member of our Search Intelligence Team, you'll architect the search and personalization systems that power Engine's core user experience. This is a unique opportunity to build sophisticated ML systems from the ground up, directly impacting conversion rates and customer satisfaction at scale.

Requirements

• 7+ years of industry experience in data science/ML engineering, with at least 4+ years specifically focused on search, ranking, and personalization systems at scale.
• Deep hands-on experience with recommendation systems, including collaborative filtering, content-based filtering, hybrid approaches, and modern deep learning techniques (neural collaborative filtering, transformer-based models, two-tower architectures).
• Proven track record building learning-to-rank models, query understanding systems, and search relevance optimization in production environments.
• Expert-level proficiency in Python (PyTorch/TensorFlow), distributed computing (Spark), and modern ML infrastructure.
• Experience with real-time serving systems and vector databases.
• Experience as a technical lead or founding member of a data science team, with the ability to balance hands-on contribution with strategic thinking and team building.
• Demonstrated success improving key business metrics (conversion, engagement, retention) through personalization, with the ability to communicate complex technical concepts to executive stakeholders.
• MS/PhD in Computer Science, Machine Learning, Statistics, or related quantitative field, or equivalent industry experience building production ML systems.

Nice To Haves

• Experience in travel, e-commerce, or marketplace platforms.
• Publications or patents in personalization, recommendation systems, or information retrieval.
• Experience with multi-objective optimization and contextual bandits.
• Knowledge of privacy-preserving personalization techniques.

Responsibilities

• Architect and build Engine's personalization engine from the ground up, implementing state-of-the-art recommendation systems, collaborative filtering, and deep learning models to deliver hyper-relevant search results and travel recommendations.
• Drive search conversion optimization through advanced ranking algorithms, query understanding, and real-time personalization, directly impacting Engine's core business metrics.
• Lead the development of user embedding and preference modeling systems that capture complex traveler behaviors, corporate policies, and contextual signals to power personalized experiences across the platform.
• Build and mentor a world-class data science team as a founding member, establishing best practices, technical standards, and a culture of experimentation and innovation.
• Partner with product, engineering, and business leaders to define the search and personalization roadmap, translating business objectives into sophisticated ML solutions.
• Design and implement A/B testing frameworks and experimentation infrastructure to rapidly iterate on personalization strategies and measure impact.
• Develop real-time inference systems that can deliver personalized results at scale with sub-second latency requirements.

Benefits

• Competitive base pay tied to role and experience, with opportunities for bonuses, commissions, and equity.
• Full list of benefits available at engine.com/culture.
• Hybrid-hub model for work environments, accommodating both office and remote work.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Master's degree
• Number of Employees: 501-1,000 employees