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# Senior Data Scientist (Availability)

- **Company:** Emerging Travel Group
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Application Programming Interfaces (APIs), Airflow, Big Data, Data Deduplication, Python (Programming Language), Machine Learning, Operational Databases, Recommender Systems, Standard Sql, Model Validation, Pyspark, Xgboost, Machine Learning Operations, Data Pipelines, Microservices
- **Published:** August 24, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/peck5bvfsl

## About the Role

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, * 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

## Description

* 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


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