Senior Machine Learning Scientist

Responsibilities

• Frame ambiguous business problems (e.g., traveler personalization, price elasticity, fraud propensity, demand forecasting, ranking/recommendations) as well-specified ML problems with clear success metrics.
• Design, train, and validate models spanning classical ML (GBMs, GLMs), deep learning (sequence models, embeddings, transformers), and causal inference / uplift modeling for pricing and marketing use cases.
• Research, adapt, or design novel ML algorithms and statistical estimators when off-the-shelf approaches fall short - custom loss functions, specialized estimators, and algorithmic optimizations for travel-scale problems.
• Design and analyze A/B tests and quasi-experiments to validate model impact; partner with Analytics/Data Science on metric selection and guardrails.
• Perform deep exploratory data analysis on large-scale travel data (bookings, clickstream, pricing, supply) using distributed compute (Spark, Databricks).
• Partner with Senior/Staff ML Engineers to translate research prototypes (notebooks) into production-ready model specs, feature definitions, and evaluation harnesses.
• Continuously monitor deployed models for drift, bias, and degradation; propose retraining/redesign strategies.
• Mentor mid-level data scientists/MLS on modeling rigor, experiment design, and statistical pitfalls.
• Communicate findings and trade-offs to product and engineering leadership in terms of business impact (conversion, revenue per visitor, margin, NPS).

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