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Lead Data Scientist

Hyatt Corporate Office Chicago, IL 🇺🇸 Remote

Chicago, IL

Today

$160k - $170k/yr Full time Ai Ml Artificial Intelligence Data

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Job Description

Lead Data Scientist, individual contributor on Hyatt's AIML team focused on Search, Personalization, and Agents.

Responsibilities

Own the design, development, evaluation, and optimization of AI and ML solutions that support Hyatt’s guest, colleague, and operational experiences.
Provide technical leadership, mentor peers, influence architecture and product direction, and raise the overall technical bar for applied AI at Hyatt.
Serve as a hands-on technical lead for high impact AI and machine learning initiatives.
Lead solution design, modeling decisions, experimentation strategy, and technical tradeoff discussions.
Partner with ML engineering and data engineering teams to deploy scalable real-time inference pipelines and batch processing workflows.
Influence technical roadmaps and help sequence data science initiatives based on business value, feasibility, risk, and team capacity.
Mentor data scientists and ML practitioners through design reviews, code reviews, modeling best practices, and knowledge sharing.
Collaborate with ML engineering to productionize models and Gen AI services using AWS-native tools and modern MLOps practices.
Contribute to scalable ML system design, including data pipelines, feature workflows, model serving, observability, monitoring, and lifecycle management.
Apply strong software engineering practices, including version control, CI/CD, testing, reproducibility, containerization, and documentation.
Support deployment patterns for both batch and low-latency inference use cases.
Partner with security, governance, architecture, and legal/privacy stakeholders to ensure AI systems are reliable, secure, compliant, and responsibly deployed.
Work closely with product owners, data scientists, ML engineers, data engineers, architects, and business stakeholders to deliver end-to-end algorithmic products.
Communicate model behavior, limitations, assumptions, risks, and business impact clearly to technical and non-technical audiences.
Define measurable success criteria and help evaluate whether AI solutions are delivering intended outcomes.
Champion responsible AI, inclusive design, and practical experimentation across projects.

Requirements

Master’s degree in computer science, software engineering, or a related field; PhD preferred.
Six or more years of experience in machine learning roles with a focus on NLP/NLU, reinforcement learning, or large language model applications.
Three or more years of people management experience in a tech leadership role.
Experience fine-tuning and deploying LLMs or other Generative AI solutions to production.
Proficiency with AWS cloud services such as SageMaker, ECS/EKS, Step Functions, Lambda, and Glue.
Strong Python programming skills, with familiarity in SQL, PySpark, and containerization using Docker.
Proven experience designing scalable data pipelines and ML systems for both real-time and batch inference.
Deep understanding of responsible AI practices, CI/CD pipelines, Agile development practices, and model lifecycle management.
Excellent interpersonal and communication skills, with a strong bias for action and collaboration.
Familiarity with ML observability and governance tools.

Technologies

Python
SQL
PySpark
Docker
SageMaker
ECS
EKS
Step Functions
Lambda
Glue

Benefits

Annual allotment of free hotel stays at Hyatt hotels globally
Flexible work schedule
Headspace subscription
Discount at on-site fitness center
Paid time off following the birth or adoption of a child
Financial assistance for adoption
Paid Time Off
Medical, Dental, Vision coverage
401K with company match

Qualifications

Master’s degree in computer science, software engineering, or a related field; PhD preferred.
Six or more years of experience in machine learning roles focused on NLP/NLU, reinforcement learning, or LLM applications, including at least three years in a tech leadership role.
Experience fine-tuning and deploying LLMs or other Generative AI solutions to production.
Expertise in AWS cloud services (SageMaker, ECS/EKS, Step Functions, Lambda, Glue).
Strong Python skills with SQL, PySpark, and Docker experience.
Proven ability to design scalable data pipelines and ML systems for real-time and batch inference.
Deep understanding of responsible AI, CI/CD, Agile methods, and model lifecycle management.
Excellent communication and collaboration skills.
Familiarity with ML observability and governance tools.

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