Senior Data Scientist

Sr. Data Scientist, Claims & Incident Analytics Location: based in Chicago / CST but open to remote candidates Duration: 3 months+ Overvie • wSenior data science role focused on machine learning and NLP solutions for claims and incident mitigation analytic s Responsibiliti • esTranslate risk management business requirements into well-defined data science solutions, including incident prioritization and claim severity classificati • onProfile, clean, and prepare claims and incident data for modeling and scori • ngDevelop feature engineering logic using structured and unstructured data sourc • esApply NLP and text-processing techniques to claim and incident narratives to extract risk signa • lsBuild record-linkage approaches to connect incidents and claims where clean unique identifiers are unavailab • leBuild and validate models that rank incidents by likelihood of escalation or intervention ne • edBuild and validate claim severity models that classify claims by financial impact and high-dollar ri • skGenerate explainability outputs including key risk drivers and business-readable flags for incidents and clai • msCollaborate cross-functionally with Legal, Data Engineering, BI, Data Governance, and MLOps partne • rsMonitor model performance, drift, scoring quality, and retraining nee • dsDocument modeling assumptions, feature logic, validation results, limitations, and handoff requiremen • tsEnsure appropriate handling of PII and sensitive data fields per governance standar • dsPresent findings and recommendations clearly to both business and technical stakeholde rs Qualificati • onsExpertise in operations research modeling (LP, IP, MIP) and solvers such as CPLEX or Gur • obiExpertise in machine learning — supervised, unsupervised, and deep learning meth • odsExpertise in feature engineering, model evaluation, and hyperparameter tun • ingProficiency in Python, SQL, and Spark; experience with Scikit-Learn, XGBoost, TensorFlow, PyTorch, MXNet, and LLM framewo • rksExperience developing and deploying solutions in cloud environments (AWS, Azure, or GCP) with large datas • etsExperience with streaming data architectures and Agile methodol • ogyFamiliarity with DevOps and CI/CD conce • ptsMaster's degree in Computer Science, Statistics, Industrial Engineering, or related field (PhD preferr • ed)5+ years of data science or operations research experience (2+ years with a P hD)