Remote Principal Data Scientist - AI & Claims Analytics

Sedgwick; Albuquerque (NM); Remote; USD 140,000 - 200,000; Full time

Job summary

Sedgwick is seeking a Principal Data Scientist to lead the design and deployment of advanced statistical and machine learning models across claims outcomes, risk management, and operational efficiency.

You will mentor junior data scientists, collaborate with AI engineering teams to productionize models, develop scalable pipelines, and translate complex analytics into actionable business insights for executives.

Qualifications

• Advanced degree in a quantitative field required.
• 8–12+ years in data science or analytics.
• Expert in ML algorithms and predictive analytics.
• Experience deploying models to production systems.
• Ability to mentor junior staff.

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 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.

Skills

Data science

Machine learning

Python

R

Production ML

Model deployment

Leadership

Communication

Education

Master's in Data Science

PhD in related field

Tools

TensorFlow

Scikit-Learn

SQL

Spark

Job description

Sedgwick is seeking a Principal Data Scientist to lead the design and deployment of advanced statistical and machine learning models across claims outcomes, risk management, and operational efficiency.

You will mentor junior data scientists, collaborate with AI engineering teams to productionize models, develop scalable pipelines, and translate complex analytics into actionable business insights for executives.