Data Scientist

Title-Data Scientist
Duration: Long-Term Contract
Location- Local to Chicago very much preferred
Interview Process: Video Interview Required
Must have:
• Claims Analytics
• Insurance Risk Modeling
• Incident Prediction
• Fraud Analytics
• Severity Modeling
• Explainable AI (SHAP, LIME, etc.)
• Hospitality Industry Analytics
• Travel Industry Analytics
• Data Governance
• PII Handling
• Data Architecture
• Databricks
• Snowflake
• Natural Language Processing
o Text Classification
o NLP Pipelines
o LLM Applications
o Claims / Incident Narrative Analysis
Operations Research & Optimization
Develop optimization solutions utilizing:
• Linear Programming (LP)
• Integer Programming (IP)
• Mixed Integer Programming (MIP)
• CPLEX
• Gurobi
• Apply mathematical optimization techniques to business and operational challenges
• Support resource allocation and decision optimization initiatives

Data Science & Advanced Analytics
• Develop predictive analytics and statistical modeling solutions
• Build record-linkage and entity-resolution models where unique identifiers do not exist
• Support large-scale data analysis across enterprise datasets
• Work with structured, semi-structured, and unstructured data sources
• 5+ years of Data Science, Machine Learning, Operations Research, or related experience
o 2+ years may be acceptable with a relevant PhD
• Proven experience building production-grade machine learning solutions
• Strong experience with predictive analytics and risk modeling
• Experience deploying models into enterprise environments
• Experience working with large datasets and scalable architectures
• Agile delivery experience

Programming & Data Technologies
• Python
• SQL
• Spark

Position Overview
Hyatt is seeking a Senior Data Scientist to lead the development of advanced Machine Learning, Natural Language Processing (NLP), Artificial Intelligence, and Operations Research solutions supporting enterprise Risk Management, Claims Analytics, Incident Mitigation, and business optimization initiatives.
This role will partner closely with Risk Management, Legal, Data Engineering, Data Governance, BI, and MLOps teams to design, deploy, and optimize predictive and optimization models that directly impact business outcomes.
This is not a reporting-focused or dashboard-oriented Data Scientist role.
Hyatt is specifically looking for a hands-on practitioner capable of building production-grade AI and Machine Learning solutions that can identify high-risk incidents, predict claim severity, optimize business decisions, and deliver explainable insights to business stakeholders.

What Hyatt Actually Needs
Hyatt is not looking for a generic Data Scientist.
They are hiring a:
AI & Risk Analytics Specialist who can build production-ready machine learning, NLP, and optimization models that help Hyatt predict, prioritize, and mitigate risk before incidents become costly claims.
The primary mission of this role is to:
• Predict which incidents are most likely to become claims
• Forecast claim severity and financial exposure
• Analyze unstructured incident and claims narratives using NLP and LLM technologies
• Develop explainable AI solutions that business stakeholders can trust
• Apply Operations Research techniques to optimize business decisions and resource allocation
• Deliver scalable production models that integrate into enterprise workflows
This role sits at the intersection of:
Risk Analytics + AI/ML + NLP + Operations Research + Business Optimization

Core Responsibilities

Machine Learning & Predictive Modeling
• Design, develop, deploy, and optimize machine learning models
• Build incident prioritization and claim severity prediction models
• Develop risk-scoring frameworks for proactive risk identification
• Perform feature engineering across structured and unstructured datasets
• Monitor model performance, drift, retraining requirements, and scoring quality

Natural Language Processing (NLP) & AI
• Develop NLP solutions for claims and incident narrative analysis
• Build text classification and language-processing pipelines
• Leverage Large Language Models (LLMs) to extract business insights
• Generate explainable AI outputs and risk-driver analysis
• Apply AI techniques to improve operational decision-making

Data Science & Advanced Analytics
• Develop predictive analytics and statistical modeling solutions
• Build record-linkage and entity-resolution models where unique identifiers do not exist
• Support large-scale data analysis across enterprise datasets
• Work with structured, semi-structured, and unstructured data sources

Cross-Functional Collaboration
• Partner with Risk Management, Legal, Data Engineering, Data Governance, BI, and MLOps teams
• Translate business requirements into technical solutions
• Present findings and recommendations to technical and executive stakeholders
• Mentor junior Data Scientists and contribute to team best practices

Documentation & Governance
• Create documentation covering methodology, assumptions, validation approaches, and limitations
• Support model governance and explainability requirements
• Ensure compliance with data governance, privacy, and security standards

Machine Learning Frameworks
• Scikit-Learn
• XGBoost
• TensorFlow
• PyTorch
• MXNet
• LLM Frameworks
Cloud Platforms
• AWS
• Azure
• GCP
DevOps & MLOps
• CI/CD
• MLOps Frameworks
• Model Deployment & Monitoring

Education
Required:
• Master's Degree in:
o Computer Science
o Statistics
o Industrial Engineering
o Operations Research
o Related Technical Field
Preferred:
• PhD in a relevant discipline

Ideal Candidate Profile
The strongest candidates will demonstrate:
• Deep Operations Research expertise
• Strong AI/ML engineering capabilities
• Hands-on NLP and LLM experience
• Experience building production machine learning systems
• Claims, risk, or incident analytics experience
• Ability to communicate complex analytical findings to business stakeholders
• Strong understanding of model explainability and governance
• Experience deploying scalable enterprise AI solutions
This role is best suited for a senior-level Data Scientist who can move beyond experimentation and deliver measurable business value through production-ready AI, NLP, and optimization solutions.