Sedgwick is a global company that provides meaningful support to individuals facing unexpected challenges. The Principal Data Scientist will lead the design and development of advanced statistical and machine learning models to enhance claims outcomes and operational efficiency.
Responsibilities:
- Lead the design and development of advanced statistical and machine learning models that improve claims outcomes, operational efficiency, and risk management
- Serve as the technical authority for complex modeling initiatives including fraud detection, claims severity prediction, litigation risk modeling, and recovery optimization
- Develop predictive and prescriptive models using structured and unstructured claims data, including adjuster notes, medical records, and policy documentation
- Architect modeling approaches that leverage modern techniques such as gradient boosting, deep learning, NLP, anomaly detection, and probabilistic modeling
- Partner with AI Engineering teams to productionize models and integrate them into enterprise AI platforms and operational systems
- Design feature engineering strategies and modeling pipelines using large-scale enterprise datasets
- Establish best practices for model development, experimentation, validation, and reproducibility
- Lead advanced analytical techniques such as causal inference, scenario simulation, and risk scoring methodologies
- Build and maintain model evaluation frameworks that measure accuracy, bias, stability, and business impact
- Monitor deployed models for drift, degradation, and changing data distributions, and recommend recalibration strategies
- Provide technical guidance to data scientists and analysts across the organization
- Mentor junior team members on statistical methods, machine learning techniques, and analytical rigor
- Translate complex analytical findings into clear, actionable insights for business leaders and operational teams
- Collaborate with Claims Operations, Finance, Risk, and IT stakeholders to identify high-impact analytical opportunities
- Evaluate external data sources and third-party analytical solutions that enhance predictive capabilities
- Ensure analytical methodologies align with enterprise governance standards and regulatory expectations
- Contribute to Sedgwick’s broader AI and advanced analytics strategy by identifying emerging technologies and modeling approaches
- Lead research and innovation initiatives that advance Sedgwick’s predictive analytics capabilities