数据科学总监
Director Data Science
加入Sedgwick,你将参与真正有意义的事业。我们的33,000名同事每天为全球面临意外的人们提供帮助。我们邀请你与我们共同成长,体验我们的关怀文化,享受工作与生活的平衡。在这里,你所能实现的没有界限。
《新闻周刊》将Sedgwick评为美国最佳职场全国顶级公司
被认证为最佳工作场所®
《财富》金融与保险行业最佳工作场所
首席数据科学家职位职责
- 领导先进统计和机器学习模型的设计与开发,以改善理赔结果、运营效率和风险管理。
- 作为复杂建模项目的技术权威,包括欺诈检测、理赔严重性预测、诉讼风险建模和追偿优化。
- 使用结构化和非结构化理赔数据开发预测和处方模型,包括理赔员笔记、医疗记录和保单文件。
- 构建利用现代技术(如梯度提升、深度学习、自然语言处理、异常检测和概率建模)的建模方法。
- 与AI工程团队合作,将模型产品化,并将其集成到企业AI平台和运营系统中。
- 使用大规模企业数据集设计特征工程策略和建模流程。
- 建立模型开发、实验、验证和可重复性的最佳实践。
- 领导高级分析技术,如因果推断、情景模拟和风险评分方法。
- 构建并维护衡量准确性、偏差、稳定性及业务影响的模型评估框架。
- 监控已部署的模型是否存在漂移、性能下降和数据分布变化,并推荐重新校准策略。
- 为组织内的数据科学家和分析师提供技术指导。
- 指导初级团队成员掌握统计方法、机器学习技术和分析严谨性。
- 将复杂的分析结果转化为清晰、可操作的见解,供管理层和运营团队使用。
- 与理赔运营、财务、风险和IT相关方合作,识别高影响力的分析机会。
- 评估外部数据源和第三方分析解决方案,以增强预测能力。
- 确保分析方法符合企业治理要求。
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By joining Sedgwick, you'll be part of something truly meaningful. It’s what our 33,000 colleagues do every day for people around the world who are facing the unexpected. We invite you to grow your career with us, experience our caring culture, and enjoy work-life balance. Here, there’s no limit to what you can achieve.
Newsweek Recognizes Sedgwick as America’s Greatest Workplaces National Top Companies
Certified as a Great Place to Work®
Fortune Best Workplaces in Financial Services & Insurance
Principal Data ScientistJob Responsibilities
- 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.
Qualifications
- 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.
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Sedgwick is an Equal Opportunity Employer and a Drug-Free Workplace.
If you're excited about this role but your experience doesn't align perfectly with every qualification in the job description, consider applying for it anyway! Sedgwick is building a diverse, equitable, and inclusive workplace and recognizes that each person possesses a unique combination of skills, knowledge, and experience. You may be just the right candidate for this or other roles.
Originally posted on Himalayas