Role: Sr Data Scientist

Location: Chicago, IL-Remote

Duration: 4+ month Contract

Client: Hyatt Corporation

Visa: GC/USC

Purpose:

The Sr Data Scientist will design and implement machine learning and NLP solutions for a claims and incident mitigation analytics project. This role will help risk management teams identify high-risk incidents earlier, classify claims by likely severity and financial impact, and provide explainable insights that support faster intervention. The position responsibilities outlined below are not all encompassing. Other duties, responsibilities, and qualifications may be required and/or assigned as necessary.

Required Skills -

• Strong experience building supervised machine learning models, especially classification, ranking, and severity / risk scoring models.
• Strong experience with data profiling, data cleaning, feature engineering, model validation, and model evaluation.
• Experience working with messy, sparse, real-world enterprise datasets.
• Strong Python and SQL skills.
• Experience with NLP or text analytics, including narrative cleaning, text classification, embeddings, keyword extraction, or summarization.
• Experience with probabilistic record linkage, entity resolution, fuzzy matching, or deduplication.
• Experience explaining model outputs using feature importance, SHAP, reason codes, or other explainability methods.
• Experience working with Snowflake or similar enterprise data warehouse platforms.
• Experience supporting batch scoring, model monitoring, and production handoff.
• Strong understanding of data governance, sensitive data handling, and PII masking or exclusion.
• Excellent communication and teamwork skills.

Preferred skills:

• Experience with insurance claims, risk management analytics, litigation analytics, fraud detection, or safety analytics.
• Experience with claim severity modeling or high-dollar claim prediction.
• Experience with AWS, SageMaker, or similar cloud-based data science environments.
• Experience supporting BI outputs in Tableau, Power BI, Looker, or similar tools.
• Familiarity with MLOps best practices, model versioning, monitoring, and retraining workflows.
• Exposure to hospitality, property operations, guest experience, or enterprise safety data.
• Proven ability to translate complex analytics into practical business workflows and measurable impact.