Data Scientist (Look-2-Book)

Emerging Travel Group operates in the travel industry.

• Lead ML projects end to end, from hypothesis formulation and task setting to measurable business impact, while maintaining production model quality and fast time to market
• Collaborate with Data Engineers to build production data pipelines and with Data Analysts to understand business context, define metrics, and design and evaluate A/B tests
• Translate travel and B2B business problems into mathematical and ML modeling tasks
• Design and deploy scoring models to predict whether search queries will convert into bookings, model how conversion likelihood changes with price and availability, and optimize the search-to-book funnel
• Optimize margin and profitability while minimizing operational incidents, and recommend trade-offs based on B2B client preferences
• Predict whether rates and offers will become stale before booking to balance data accuracy, speed, and system load
• Develop, train, and validate machine learning models to test product hypotheses and improve the B2B user experience

• At least 4 years of hands-on experience as a Data Scientist or ML Engineer
• Ability to investigate data, identify underlying business problems, and translate business objectives into clear ML tasks
• Solid knowledge of classic machine learning, including Gradient Boosting (CatBoost/LightGBM), classification, and regression
• Proven experience with entity matching and strong understanding of recommendation systems and ranking approaches, including KNN, FAISS, Learning-to-Rank, and pointwise, pairwise, and listwise methods
• Experience working with massive datasets, excellent SQL skills, and practical experience building pipelines with PySpark
• Ability to write production-quality Python code and tests, and bring models to production
• Knowledge of Airflow and Python microservices

Будет плюсом:

• TravelTech, E-commerce, or B2B API experience, including knowledge of hotels, rates, and distributors; basic NLP skills and understanding of text embeddings and how to train them; experience with dynamic pricing, multi-objective optimization, or Next Best Action (NBA) systems; a solid foundation in probability theory and mathematical statistics for experiment design and model evaluation

• Flexible work schedule with no fixed 9:00 AM start time; results are the priority
• Choose to work fully remotely, from an office, or in a hybrid model
• Individual adaptation and training programs, including soft skills and leadership development
• Partial compensation for external training and conferences
• Group and individual English lessons and speaking clubs
• Corporate prices on hotels and other travel services
• An extra MyTime Day Off to focus on health, mental recharge, personal matters, or other important activities