Hotel Engine

Staff Data Scientist, Search and Personalization

Hotel Engine

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Salary

💰 $210,000 - $245,000 per year

Job Level

Lead

Tech Stack

PythonPyTorchSparkTensorflow

About the role

  • Architect and build Engine's personalization engine using recommendation systems, collaborative filtering, and deep learning models.
  • Drive search conversion optimization via advanced ranking algorithms, query understanding, and real-time personalization.
  • Lead development of user embedding and preference modeling systems capturing traveler behaviors, corporate policies, and contextual signals.
  • Build and mentor a world-class data science team as a founding member, establishing best practices and technical standards.
  • Partner with product, engineering, and business leaders to define the search and personalization roadmap and translate objectives into ML solutions.
  • Design and implement A/B testing frameworks and experimentation infrastructure to measure impact and iterate rapidly.
  • Develop real-time inference systems to deliver personalized results at scale with sub-second latency.
  • Architect sophisticated ML systems from the ground up to directly impact conversion rates and customer satisfaction at scale.

Requirements

  • 7+ years of industry experience in data science/ML engineering.
  • 4+ years specifically focused on search, ranking, and personalization systems at scale.
  • Deep hands-on experience with recommendation systems (collaborative filtering, content-based, hybrid approaches).
  • Experience with 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.
  • Expert-level proficiency in Python (PyTorch/TensorFlow).
  • Experience with distributed computing (Spark) and modern ML infrastructure.
  • Experience with real-time serving systems and vector databases.
  • Experience building user embedding and preference modeling systems.
  • Experience designing and implementing A/B testing frameworks and experimentation infrastructure.
  • Experience developing real-time inference systems with sub-second latency requirements.
  • Experience as a technical lead or founding member of a data science team and mentoring others.
  • Demonstrated success improving business metrics (conversion, engagement, retention) through personalization.
  • MS/PhD in Computer Science, Machine Learning, Statistics, or related quantitative field, or equivalent industry experience.
  • Bonus: experience in travel, e-commerce, or marketplace platforms; publications or patents in personalization or IR; multi-objective optimization and contextual bandits; knowledge of privacy-preserving personalization techniques.