AI/ML Data Scientist with in Claims/Insurance/NLP

Please find below the Job description and share your latest resume if you are interested? Position: AI/ML Data Scientist with in Claims/Insurance/NLP Location: 100% Remote (Chicago IL) Visa Status: Independent Consultant Duration: Long Term Contract and Can convert into CTH PREFERRED TO WORK ON W2 OR 1099 Job Description: Senior Data Scientist – AI, Machine Learning, NLP & Risk Analytics. This is really a Risk Analytics + AI/ML Scientist role disguised as a Data Scientist position. The strongest candidates will come from insurance, claims analytics, fraud analytics, risk modeling, or operational research backgrounds—not generic marketing, customer analytics, or BI-focused data scientists. Must Have Required Skills: 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 Client 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. Client is specifically seeks 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 the Client Actually Needs Client 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 Thanks and Regards Karan Rajput | US IT Recruiter Desk: 609-973-8207 || KRajput@kpgtech.com