Remote Principal Data Scientist — Predictive Analytics

Sedgwick; Southaven (MS); Remote; USD 150,000 - 210,000; Full time

Job summary

Sedgwick is seeking a Principal Data Scientist to lead the design and deployment of advanced statistical and machine learning models for claims, risk, and operational optimization. You’ll act as a technical authority on complex analytics initiatives, guiding teams across data science, engineering, and business units.

You will build predictive and prescriptive models using diverse claims data, architect modern modeling pipelines, and establish best practices for validation, experimentation, and

Qualifications

• Master’s or PhD in Data Science, Statistics, Mathematics, Computer Science, Economics, or related quantitative discipline.
• 8–12+ years of experience in data science, statistical modeling, or advanced analytics roles.
• Deep expertise in machine learning algorithms, statistical modeling techniques, and predictive analytics methodologies.
• Strong programming skills in Python, R, or similar analytical languages.
• Extensive experience with large, complex datasets in enterprise environments.
• Experience designing end-to-end modeling pipelines and production deployment.

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 using gradient boosting, deep learning, NLP, anomaly detection, and probabilistic modeling.
• Partner with AI Engineering teams to productionize models and integrate 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 recalibrate as needed.
• Provide technical guidance to data scientists and analysts across the organization.
• Mentor junior team members on statistical methods 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 methodologies align with governance standards and regulatory expectations.
• Contribute to Sedgwick’s broader AI and analytics strategy by identifying emerging technologies.

Skills

Python

R

Machine learning

Statistical modeling

End-to-end modeling

Production deployment

Big data

Education

Master’s or PhD in Data Science/Statistics/Math/CS

Tools

None

Job description

Sedgwick is seeking a Principal Data Scientist to lead the design and deployment of advanced statistical and machine learning models for claims, risk, and operational optimization. You’ll act as a technical authority on complex analytics initiatives, guiding teams across data science, engineering, and business units.

You will build predictive and prescriptive models using diverse claims data, architect modern modeling pipelines, and establish best practices for validation, experimentation, and