Seeking a Data Scientist/Machine Learning Semi Senior to develop data - based solutions in Buenos Aires. Must have strong Python skills and experience in Machine Learning.
About the role
- AI Engineering leader tasked with implementing Gen AI solutions for Hyatt. Collaborating cross-functionally to innovate and enhance the guest experience through data-driven decisions.
Responsibilities
- Design and implement Gen AI solutions and partner closely with ML Engineering, Personalization, Forecasting, and Decision Science domains.
- Work cross-functionally with various data science teams, data engineering teams, and data architecture teams.
- Be a hands-on technical leader skilled as an implementation engineer while also leading the team to innovate and build cutting-edge Gen AI products and services.
- Analyze model behavior, diagnose failure modes, and iterate on data, features, and architectures to improve performance and robustness.
- Document modeling assumptions, evaluation results, and trade-offs to support reproducibility and cross-team collaboration.
Requirements
- Master’s or Ph.D. in Computer Science, Data Science, Statistics, Applied Mathematics, Machine Learning, or a closely related field.
- Strong theoretical and practical foundation in: o Supervised and unsupervised learning o Probability and statistics o Optimization and linear algebra
- Proficiency in Python for data analysis, feature engineering, and model development.
- Hands-on experience with at least one ML framework such as PyTorch, TensorFlow, or scikit-learn.
- Experience working with SQL and large-scale datasets.
- Familiarity with model evaluation, error analysis, and experiment design.
- Academic, internship, or project experience in one or more of the following: o Search relevance and ranking models o Information retrieval (lexical and semantic) o Recommender systems (collaborative filtering, content-based, hybrid) o Agentic implementations preferably user-facing
- Exposure to deep learning architectures (e.g., transformers, bi-encoders and cross-encoders).
- Understanding of offline and online evaluation methodologies, including A/B testing.
- Experience using cloud or distributed computing environments (e.g., AWS, Spark, Ray) through coursework or projects.
- Familiarity with model deployment concepts such as batch inference, real-time APIs, and model monitoring (conceptual understanding sufficient).
- Strong analytical thinking and ability to translate ambiguous product problems into well-defined modeling tasks.
Benefits
- Annual allotment of free hotel stays at Hyatt hotels globally
- Flexible work schedules
- Work-life benefits including well-being initiatives such as a complimentary Headspace subscription, and a discount at the on-site fitness center
- A global family assistance policy with paid time off following the birth or adoption of a child as well as financial assistance for adoption
- Paid Time Off, Medical, Dental, Vision, 401K with company match
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