Job Opportunities API

End-to-End ML Ownership: Lead ML projects from formulating hypotheses and task setting to delivering measurable business impact. You will be responsible for the entire cycle, ensuring fast time-to-market and maintaining model quality in production. Cross-functional Collaboration: Work closely with Data Engineers to build robust production data pipelines, and with Data Analysts to dive into business context, define metrics, and design/evaluate A/B tests. Domain-Specific Problem Solving: Translate business goals into mathematical models. You will solve core domain challenges, such as: Rate Matching (deduplication of rates from 350+ suppliers), Alternative Search (RecSys & Ranking for unavailable rates), Multi-objective Optimization (balancing margin maximization with incident minimization), and Cache Freshness Prediction (predicting the likelihood of a rate changing before booking). Model Development: Develop, train, and validate machine learning models to test product hypotheses and proactively improve the B2B user experience. Requirements Must Have: Experience: At least 4+ years of hands-on experience as a Data Scientist or ML Engineer. Business Mindset: Ability to dig into data, identify root business problems, and translate business objectives into clear ML tasks rather than just tuning metrics in a vacuum. ML Stack & Algorithms: Solid knowledge of classic Machine Learning (Gradient Boosting like CatBoost/LightGBM, Classification, Regression). Matching, RecSys & Ranking: Proven experience with entity matching tasks, and a deep understanding of Recommendation Systems and Ranking approaches (KNN, FAISS, Learning-to-Rank, pointwise / pairwise / listwise approaches). Big Data Stack: Confident experience working with massive datasets (we process terabytes daily). Excellent SQL skills and practical experience building pipelines with PySpark. Engineering Independence: Production-quality Python code, ability to write tests, and readiness to bring models to production (experience with Airflow and Python microservices). Nice to Have: Industry Experience: Experience in TravelTech, E-commerce, or B2B APIs (understanding of hotels, rates, distributors). NLP & Embeddings: Basic NLP skills, understanding the principles of text embeddings and how to train them (highly useful for matching textual rate descriptions, room types, and cancellation policies). Optimization & Pricing: Experience with dynamic pricing, multi-objective optimization, or Next Best Action (NBA) systems. Math & Stats: A solid foundation in probability theory and mathematical statistics for rigorous experiment design and model evaluation. Benefits A fully flexible work schedule — there’s no pressure to start work at exactly 9:00 AM; what matters is achieving results and moving forward; Each person in our team is encouraged to choose their preferred work format. You can work fully remotely, come to the office, or choose a hybrid work model; We are an ambitious and supportive team who love what they do, appreciate each other, and grow together; The growth and development of each employee is our priority, so we have internal programs available for adaptation and training, development of soft skills and leadership abilities that are tailored individually to each employee; We also provide partial compensation for employees participating in external training and conferences; In tourism, it's difficult to grow without an excellent knowledge of English, and we support our employees' language learning goals — we organize group and individual lessons, plus speaking clubs with colleagues from all over the world; And, of course, to encourage you to travel more, we offer corporate prices on hotels and other travel services; We prioritize well-being and are committed to supporting the overall health and work-life balance at ETG. As part of this commitment, we provide MyTime Day Off - an extra day off that is designed to gi