Data Scientist - Remote

About The Company

Sedgwick is a global leader in risk and claims management, committed to helping clients navigate the complexities of the unexpected. With a workforce of over 33,000 dedicated professionals and a diverse client base spanning 80 countries, Sedgwick sets the standard for innovative solutions in claims administration, loss adjusting, benefits management, and product recall. Recognized as one of America’s Greatest Workplaces by Newsweek, a Great Place to Work®, and among Fortune’s Best Workplaces in Financial Services & Insurance, Sedgwick fosters a caring culture that values growth, diversity, and work-life balance. The company leverages advanced AI-enabled technology and industry expertise to deliver impactful outcomes, ensuring clients thrive amidst a rapidly changing risk landscape.

About The Role

We are seeking a Principal Data Scientist to join our dynamic analytics team. In this role, you will lead the design and development of sophisticated statistical and machine learning models aimed at enhancing claims outcomes, operational efficiency, and risk management. You will serve as a technical authority for complex modeling initiatives such as fraud detection, claims severity prediction, litigation risk assessment, and recovery optimization. Your expertise will help translate large and diverse datasets—including structured data, unstructured claims notes, medical records, and policy documents—into actionable insights that drive strategic decision-making. Collaborating closely with AI engineering, claims operations, finance, risk, and IT teams, you will ensure models are effectively integrated into enterprise systems, monitored for performance, and continuously improved. This role offers an exciting opportunity to lead innovation in predictive analytics, mentor junior team members, and contribute to Sedgwick’s broader AI strategy, ultimately helping shape the future of risk management solutions.

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 roles
• Deep expertise in machine learning algorithms, statistical techniques, and predictive modeling methodologies
• Proficiency in programming languages such as Python, R, or similar analytical tools
• Extensive experience working with large, complex datasets within enterprise environments
• Proven track record of designing and deploying end-to-end modeling pipelines
• Strong understanding of model validation, feature engineering, and performance evaluation
• Experience collaborating with engineering teams to operationalize models in production systems
• Knowledge of distributed data processing tools and modern data platforms (preferred)
• Experience in insurance, claims management, healthcare, or financial services analytics (preferred)
• Excellent communication skills to convey complex concepts to technical and non-technical audiences
• Leadership and mentoring capabilities to guide junior team members

Responsibilities

• Lead the design and development of advanced statistical and machine learning models to improve claims outcomes and operational efficiency
• Act as the technical authority for complex modeling projects including fraud detection, claims severity prediction, and litigation risk modeling
• Develop predictive and prescriptive models utilizing structured and unstructured data sources
• Architect innovative modeling approaches leveraging 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 platforms and operational systems
• Design feature engineering strategies and develop scalable modeling pipelines using large enterprise datasets
• Establish best practices for model development, experimentation, validation, and reproducibility
• Lead analytical initiatives involving causal inference, scenario simulation, and risk scoring methodologies
• Build and maintain model evaluation frameworks to assess accuracy, bias, stability, and business impact
• Monitor deployed models for drift, degradation, and data distribution changes; recommend recalibration strategies
• Provide technical guidance and mentorship to data scientists and analysts across the organization
• Translate complex analytical insights into clear, actionable recommendations for business teams
• Collaborate with cross-functional stakeholders to identify high-impact analytical opportunities
• Evaluate external data sources and third-party solutions to enhance predictive capabilities
• Ensure all analytical methodologies comply with enterprise governance standards and regulatory requirements
• Contribute to Sedgwick’s AI and analytics strategy by exploring emerging technologies and modeling approaches
• Lead research initiatives to advance predictive analytics capabilities within the organization

Benefits

• Competitive salary and performance-based incentives
• Comprehensive health insurance plans including medical, dental, and vision coverage
• Retirement savings plans with company matching contributions
• Generous paid time off and holiday leave
• Opportunities for professional development and continuous learning
• Flexible work arrangements and remote working options
• Access to cutting-edge technology and resources for innovation
• Supportive and inclusive company culture that promotes diversity and growth

Equal Opportunity

Sedgwick is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or any other protected status in accordance with applicable laws and regulations.