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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Data Scientist - **Company:** Sedgwick - **Location:** Albuquerque, NM, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Big Data, Computer Programming, Data Infrastructure, Distributed Computing Environment, Python (Programming Language), Machine Learning, Feature Engineering, Model Validation, Information Technology, Machine Learning Operations - **Published:** September 1, 2026 - **Apply:** https://dejobs.org/x/x/6CC7ABA6E9EE4538958064E0AAD6880B/job/ ## About the Role * 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 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. * Familiarity with distributed data processing tools and modern data platforms preferred. * Experience in insurance, claims management, healthcare, or financial services analytics preferred. * Ability to communicate advanced analytical concepts to both technical and non-technical stakeholders. * Demonstrated ability to lead complex analytical initiatives that drive measurable business value. * Strong mentoring and technical leadership capabilities. #LI-TS1 #remote ## Description * 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. ## Related Videos - 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