Senior Data Scientist (Look-2-Book)

HireHi; United States; Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Remote work options

Hybrid work opportunities

English lessons

MyTime Day Off

Travel discounts

Job summary

Emerging Travel Group ищет опытного специалиста по данным: Data Scientist/ML Engineer для ведения проектов от гипотез до измеримого влияния на бизнес в travel/B2B контексте.

Кандидат будет сотрудничать с Data Engineers и Analysts, строить ML-модели, оценки и A/B-тесты, чтобы оптимизировать конверсию поиска и маржу, при этом обеспечить масштабируемость и качество моделей.

Qualifications

• 4+ года опыта в роли Data Scientist или ML Engineer
• Умение переводить бизнес-задачи в задачи ML
• Глубокие знания классического ML: градиентный бустинг, классификация и регрессия
• Опыт сопоставления сущностей и понимание рекомендаций/ранжирования (KNN, FAISS, Learning-to-Rank)
• Опыт работы с большими данными, SQL и пайплайнами на PySpark
• Умение писать продакшн-код на Python и тесты; разворачивание моделей в продакшн
• Знание Airflow и микросервисов на Python

Responsibilities

• Ведущий ML-проекты от идеи до бизнес-эффекта и поддержания качества моделей
• Сотрудничество с Data Engineers для построения production data pipelines и Data Analysts для определения метрик и A/B тестов
• Перевод бизнес-задач Travel и B2B в ML-задачи
• Разработка и развёртывание скоринговых моделей для предсказания конверсии поиска в бронирование
• Оптимизация маржи и прибыльности с учётом устойчивости к инцидентам
• Разработка, обучение и валидация моделей для улучшения B2B UX

Skills

Data Scientist / ML Engineer

Machine Learning

Recommendation Systems

SQL / PySpark

Python Production Code

Airflow

Tools

CatBoost

LightGBM

FAISS

KNN

Learning-to-Rank

Job description

Описание:

Emerging Travel Group operates in the travel industry.

Задачи:

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

Требования:

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

Условия:

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