Senior Data Scientist

MUST Have Skillsets: Hospitality experience, Building Incident & Claim Management Model

Our client is seeking an Senior Data Scientist to join their team. As a Senior Data Scientist you will design and implement AI, Machine Learning, and Operations Research models that transform business objectives into data-driven solutions. This role advances mission by optimizing decisions, improving operations, and enhancing guest experiences through applied analytics and innovation. The position responsibilities outlined below are not all encompassing. Other duties, responsibilities, and qualifications may be required and/or assigned as necessary.

Position Responsibilities:

• Translate risk management business requirements into well-defined data science solutions, including incident prioritization and claim severity classification.
• Profile, clean, and prepare claims and incident data for analytics, modeling, and scoring.
• Develop feature engineering logic using structured and unstructured claims and incident data.
• Apply NLP and text-processing techniques to claim and incident narratives to extract useful risk signals.
• Develop record-linkage approaches to connect incidents and claims when a clean unique identifier is not available.
• Build and validate models that rank incidents by likelihood of becoming claims or requiring Risk Management intervention.
• Build and validate claim severity models that classify claims by likely financial impact and high-dollar claim risk.
• Generate explain ability outputs, including key risk drivers and business-readable reasons for flagged incidents or claims.
• Collaborate with Risk Management, Legal, Data Engineering, BI, Data Governance, and MLOps partners to deliver usable business outputs.
• Monitor model performance, drift, scoring quality, and retraining needs.
• Document modeling assumptions, feature logic, validation results, limitations, and handoff requirements.
• Ensure data science work follows data governance expectations, including appropriate handling of PII and sensitive fields.
• Present findings, model results, and recommendations to business and technical stakeholders in a clear, actionable manner.

Experience And Qualifications:

Required Skills -

• Expertise in operations research modeling (LP, IP, MIP) and tools (CPLEX, Gurobi, etc).
• Expertise in building machine learning models, including supervised, unsupervised, and deep learning methods.
• Expertise in feature engineering, model evaluation, and hyperparameter tuning.
• Expertise in Python, SQL, and Spark, and a broad array of machine learning frameworks (Scikit-Learn, XGBoost, Tensorflow, PyTorch, MXNet, LLM, etc).
• Experience in developing and deploying solutions in a Cloud environment (AWS, Azure, Google Cloud Platform) 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.

Preferred Skills:

• Exposure to hospitality, travel, or service industry data and optimization use cases.
• Strong understanding of data architecture and MLOps best practices.
• Proven ability to translate complex analytics into business impact.
• Passion for continuous learning and innovation in applied data science.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.