Chicago, United States
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Salary Range (monthly):
USD 1 to 2,000
Salary Description: Competetive Salary Offered
Job Description For Data Scientist
Hyatt seeks an extraordinary data scientist to help build the algorithmic assets and features that Hyatt guests, members, customers and internal users leverage to transform the guest experience and drive efficiencies across the operations of our business.
In this role you will have the opportunity to work on a wide variety of data science projects with a focus on deploying algorithmic products that drive business impact.
You will be a part of a ground-floor, hands-on, highly visible team which is positioned for growth and is highly collaborative and passionate about data science.
- Support a variety of algorithmic products with core algorithmic data science capabilities
- Hands-on developer of internal models/processes such as machine learning models, numerical optimization, time-series forecast, statistical significance testing, ml-as-a-service API development, and streaming event data processing.
- Stay up to date with latest data science research and how it can be applied to Hyatt's business.
- Work collaboratively with other data scientists and ML engineers to ensure proper execution/integration of algorithmic products.
- Report on algorithmic product performance and incremental business impact with a commitment to ethical data science.
- Master's degree in computer science, statistics, or related fields required.
- 2-3 years of data science experience with a focus on algorithmic data science, hospitality experience not required.
- Expertise in Python and SQL, additional software experience preferred ie Docker, Spark.
- Experience in machine learning modelling (classification, regression, reinforcement) across a variety of implementations (linear, neural networks, svm, tree-based, bandits, etc) and frameworks (Tensorflow, PyTorch, Sagemaker, Prophet etc)
- Experience applying statistical test (t-test, chi-squared, non-parametric etc), experiment design, and causal inference models to real-world problems
- Experience with IP/MIP/QP optimization
- Experience deploying ml-driven solutions to production with a focus on measurable impact and outcomes
- Experience operating in a cloud environment (AWS, GCP) with large datasets.
- Experience with streaming data architectures.
- Experience operating in an Agile Methodology environment.
- Experience with DevOps and CI/CD concepts.
- Excellent communication and teamwork skills.
- Education: Master's or Ph.D. degree (top-tier research institutions, in Math, Statistics, Hard Science, Computer Science, Engineering or other closely related disciplines preferred)