Emerging Travel Group is hiring a Senior Data Scientist to lead end-to-end ML projects addressing core Availability problems in travel (rate matching, alternative search, ranking, cache freshness, pricing/optimization).

Responsibilities:

  • Lead ML projects from hypothesis and task formulation to production deployment and measurable business impact.
  • Collaborate with Data Engineers to build production data pipelines and with Data Analysts to define metrics and design/evaluate A/B tests.
  • Translate business goals into mathematical models for problems such as rate deduplication, recommendation & ranking, multi-objective optimization, and cache freshness prediction.
  • Develop, train, validate and maintain machine learning models in production.

Key requirements (Must have):

  • At least 4+ years of hands-on experience as a Data Scientist or ML Engineer.
  • Strong business mindset: translate business objectives into ML tasks.
  • Solid knowledge of classic ML and Gradient Boosting (CatBoost/LightGBM), classification and regression.
  • Experience with matching, recommendation systems and ranking approaches (KNN, FAISS, learning-to-rank: pointwise/pairwise/listwise).
  • Experience working with big data (terabyte-scale), excellent SQL and practical experience building pipelines with PySpark.
  • Production-quality Python code, tests, and experience bringing models to production (Airflow, Python microservices).

Nice to have:

  • Experience in TravelTech, e‑commerce or B2B APIs.
  • Basic NLP and embeddings knowledge.
  • Experience with dynamic pricing, multi-objective optimization or Next Best Action systems.
  • Strong foundation in probability theory and mathematical statistics for experiment design and evaluation.

We offer:

  • Fully flexible work schedule and choice of work format: fully remote, office or hybrid.
  • Support for growth and training, partial compensation for external training and conferences.
  • Language learning support, corporate prices on travel services, and additional MyTime Day Off.