We are seeking a Senior Data Scientist to lead the development of personalization models that power our AI agents. In this role, youll design and deploy intelligent systems that understand each travelers preferences, intent, and behaviortransforming complex user journeys into effortless, hyper-personalized experiences.This is a high-impact, cross-functional role working closely with product managers, engineers, designers, and the AI/LLM platform team to create deeply personalized, autonomous travel assistance that feels like magic (but is all math and modeling underneath).
What Youll Do:
Design and build machine learning models that power personalization across our agentic platform, including traveler profiles, flights & hotels recommendation engines, and behavioral prediction systems.
Develop algorithms that adapt and learn from user behavior over time, channels, and modalities (text, voice, action).
Collaborate with PMs, engineers, and conversational designers to integrate ML into real-time decision loops, conversational agents, and proactive UX flows.
Own experimentation pipelines and performance evaluation, AB tests, offline metrics, and production agent behavior.
Work hands-on with structured and unstructured data (e.g., travel history, chat logs, user feedback, booking behavior) to extract insights and drive model improvement.
Define and maintain robust MLops practices: monitoring, retraining, feature pipelines, and real-time inference.
Stay current with the latest in recommender systems, LLM integration, embeddings, retrieval augmentation, and agentic reasoning to continuously evolve our approach.
Requirements: 5+ years of experience in applied data science or machine learning roles, with a strong focus on personalization, recommender systems, or predictive modeling.
Advanced degree (MS/PhD) in Computer Science, Machine Learning, Statistics, or a related field, or equivalent hands-on experience.
Proficiency in Python and ML frameworks
Strong grounding in data pipelines and working knowledge of tools such as SQL, Spark, Airflow, and modern MLOps stacks.
Experience building real-time or near-real-time recommendation systems at scale.
Bonus points for working with conversational agents, LLM-based systems (e.g. RAG, prompt engineering), or user embeddings.
Passion for crafting user-centric AI, and curiosity about human behavior in the context of travel
Ability to communicate technical concepts clearly and collaborate cross-functionally with product, design, and engineering teams.
This position is open to all candidates.