
High Salary Senior Data Scientist
4 weeks ago
We are seeking a highly motivated Applied Scientist / Machine Learning Engineer to join our Data Science team. This individual will play a key role in enhancing and scaling our existing ML systems and developing new capabilities that support our intelligent decision-making platform.
We are looking for team members who:
● Are deeply curious and passionate about applying machine learning to real-world problems.
● Demonstrate strong ownership and the ability to work independently.
● Excel in both technical execution and collaborative teamwork.
● Have a track record of shipping products in complex environments.
What You'll Do
● Build, train, and deploy machine learning models for forecasting, pricing, and optimization.
● Apply advanced techniques like causal inference, counterfactual analysis, and reinforcement learning to improve decision-making under uncertainty.
● Work with large-scale, noisy, and temporally complex datasets.
● Collaborate cross-functionally with engineering and product teams to move models from research to production.
● Design offline evaluation frameworks and simulations to validate new algorithms before live rollout.
● Generate interpretable and trusted outputs to support adoption of AI-driven rate recommendations.
● Contribute to the development of an AI-first platform that redefines hospitality revenue management.
Required Qualifications :
● Bachelor's or Master's degree in Computer Science or related field.
● 5–10 years of hands-on experience in a product-centric company, ideally with full model lifecycle exposure.
● Demonstrated ability to apply machine learning to solve real-world business problems.
● Proficient in Python and machine learning libraries such as scikit-learn, PyTorch, and XGBoost.
● Strong knowledge of forecasting models (time-series and ML-based).
● Deep understanding of machine learning and deep learning foundations.
● Comfort with optimization under uncertainty and experience in evaluating ML model performance rigorously.
● Ability to work independently and manage projects end-to-end.
Preferred Experience
● Experience in revenue management, pricing systems, or demand forecasting, particularly within the hotel and hospitality domain.
● Applied knowledge of reinforcement learning techniques (e.g., bandits, Q-learning, model-based control).
● Familiarity with causal inference methods (e.g., DAGs, treatment effect estimation).
● Strong written and verbal communication skills to explain complex technical concepts clearly to cross-functional teams.
● Proven experience in collaborative product development environments, working closely with engineering and product teams.
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