Principal Data Scientist

🕒 Maio 1

🥔 Idaho, Nebraska, +2 estados a mais – Remoto

🥔 Idaho – Remote 🌾 Nebraska – Remote 🏰 Missouri – Remote 🎸 Tennessee – Remote

⏰ Tempo Integral

🔴 Especialista

📊 Cientista de Dados

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Sedgwick

SiteLinkedInTodas as Vagas

10.000+ funcionários

🏢 Corporativo

📋 Conformidade

Insurance • Enterprise • Compliance

A Sedgwick é uma fornecedora global de soluções de tecnologia para riscos, benefícios e negócios integrados. Eles ajudam pessoas e organizações a gerenciar e mitigar riscos com soluções em administração de sinistros de acidentes, saúde, invalidez, compensação por desemprego e responsabilidade, entre outros. A Sedgwick oferece serviços como administração de sinistros, consultoria de construção, contabilidade forense e engenharia forense. Suas especialidades incluem restauração de propriedades, proteção de marcas e prevenção de perdas em vários setores, incluindo agricultura, construção e setores ambientais. A empresa enfatiza diversidade, equidade e inclusão (DEI) e práticas ambientais, sociais e de governança (ESG).

Descrição

• 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.

🎯 Requisitos

• 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.

🏖️ Benefícios

• Work-life balance • Professional development opportunities