Principal Data Scientist

Job not on LinkedIn

🕒 May 1

🥔 Idaho, Nebraska, +2 more states – Remote

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

⏰ Full Time

🔴 Lead

📊 Data Scientist

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 45%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Sedgwick

WebsiteLinkedInAll Job Openings

10,000+ employees

🏗️ Construction

💼 Consulting

🏥 Healthcare

Construction • Consulting • Healthcare

Sedgwick is a global provider of technology-enabled risk, benefits, and integrated business solutions. They help people and organizations by managing and mitigating risk with solutions in accident, health, disability, unemployment compensation, and liability claims administration, among others. Sedgwick offers services such as claims administration, building consulting, forensic accounting, and forensic engineering. Their specialties include property restoration, brand protection, and loss prevention across several industries, including agriculture, construction, and environmental sectors. The company emphasizes diversity, equity, and inclusion (DEI) as well as environmental, social, and governance (ESG) practices.

📋 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.

🎯 Requirements

• 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.

🏖️ Benefits

• Work-life balance • Professional development opportunities