Data Scientist

Job Title: Senior Data Scientist AI, Machine Learning, NLP & Risk Analytics.

Duration: Long-Term Contract

2 open positions

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

• Text Classification
• NLP Pipelines
• LLM Applications
• 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

• 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:

• Computer Science
• Statistics
• Industrial Engineering
• Operations Research
• 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.

Work Environment

Remote position

Must support U.S. business hours

Enterprise AI and analytics environment

Cross-functional collaboration with Risk, Legal, Data Engineering, Governance, and Business stakeholders

High-visibility initiatives supporting business optimization and risk mitigation

Interview Process

Video Interview Required

Technical deep-dive expected

Discussion of ML, NLP, Operations Research, and production deployment experience

Evaluation of stakeholder communication and business problem-solving capabilities

Mandatory Candidate Submission Requirements

All Candidates Must Provide

Updated Resume

Full Legal Name

Contact Number

Email Address

Current Location

Work Authorization Status

LinkedIn Profile

Availability to Interview

Availability to Start

Expected Rate (Maximum $100/hr C2C)

Education Details (Highest Degree Earned)

Compliance Requirements

All submitted information must be complete, accurate, and verifiable.

Candidates should be prepared to provide identity verification documentation during onboarding if requested by the client.

Any discrepancies involving employment history, education, work authorization, certifications, location, or identity verification may result in:

Immediate disqualification

Removal from consideration

Vendor escalation if submitted information is found to be inaccurate