Data Scientist -WFH

About the Company
Sedgwick provides services that support people and organizations when they face unexpected challenges. With 33,000 colleagues worldwide, the company emphasizes a caring culture, work-life balance, and professional growth. Sedgwick has been recognized by Newsweek as one of America's Greatest Workplaces National Top Companies, is certified as a Great Place to Work®, and has been recognized among Fortune's Best Workplaces in Financial Services & Insurance.
About the Role
Sedgwick is seeking a Principal Data Scientist to lead advanced analytics and machine learning initiatives that improve claims outcomes, operational efficiency, and risk management. This role will serve as the technical authority for complex modeling projects, including fraud detection, claims severity prediction, litigation risk modeling, and recovery optimization.
The Principal Data Scientist will develop predictive and prescriptive models using structured and unstructured claims data, work with AI Engineering teams to bring models into production, and establish standards for model development, validation, and monitoring. The role also includes mentoring data scientists and analysts, advising business leaders, and contributing to Sedgwick's broader AI and advanced analytics strategy.
Key Responsibilities
Lead the design and development of advanced statistical and machine learning models for claims outcomes, operational efficiency, and risk management.
Provide technical leadership for modeling initiatives involving fraud detection, claims severity prediction, litigation risk, and recovery optimization.
Develop predictive and prescriptive models using claims data, including adjuster notes, medical records, and policy documentation.
Design modeling approaches using gradient boosting, deep learning, natural language processing (NLP), anomaly detection, and probabilistic modeling.
Partner with AI Engineering teams to productionize models and integrate them into enterprise AI platforms and operational systems.
Develop feature engineering strategies and modeling pipelines using large-scale enterprise datasets.
Establish best practices for model development, experimentation, validation, and reproducibility.
Apply advanced analytical methods, including causal inference, scenario simulation, and risk scoring.
Build and maintain model evaluation frameworks to measure accuracy, bias, stability, and business impact.
Monitor deployed models for drift, performance degradation, and changes in data distributions, and recommend recalibration strategies.
Provide technical guidance to data scientists and analysts across the organization.
Mentor junior team members in 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 to enhance predictive capabilities.
Ensure analytical methodologies comply with enterprise governance standards and regulatory expectations.
Contribute to Sedgwick's AI and advanced analytics strategy by identifying emerging technologies and modeling approaches.
Lead research and innovation initiatives to advance predictive analytics capabilities.
Required Qualifications
Master's or PhD in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related quantitative discipline.
8–12+ years of experience in data science, statistical modeling, or advanced analytics.
Deep expertise in machine learning algorithms, statistical modeling, and predictive analytics methodologies.
Strong programming skills in Python, R, or similar analytical languages.
Extensive experience working with large, complex datasets in enterprise environments.
Proven experience designing and implementing end-to-end modeling pipelines.
Strong understanding of model validation, feature engineering, and performance evaluation techniques.
Experience collaborating with engineering teams to deploy models into production systems.
Ability to communicate advanced analytical concepts to technical and non-technical stakeholders.
Demonstrated ability to lead complex analytical initiatives that deliver measurable business value.
Strong mentoring and technical leadership capabilities.
Preferred Qualifications
Familiarity with distributed data processing tools and modern data platforms.
Experience in insurance, claims management, healthcare, or financial services analytics.
Work Arrangement
Remote
Additional Information
Sedgwick is an Equal Opportunity Employer and a Drug-Free Workplace. The company encourages candidates to apply even if their experience does not align with every qualification listed, recognizing that individuals bring different combinations of skills, knowledge, and experience to the role. Candidates may also be considered for other suitable opportunities within the organization.

Work arrangement
Yes