Sedgwick

Principal Data Scientist

Sedgwick • $130K — $160K *
US-Anywhere
+ 27 other locationsRemote
Finance & Insurance
8 - 10 years of experience
Reposted Today
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Job Overview by Ladders

Qualifications

  • Master's or PhD in Data Science, Statistics, Mathematics, Computer Science, Economics, or related quantitative field.
  • 10+ years in data science, advanced analytics, or quantitative modeling.
  • 5+ years in leadership within data science or analytics teams.
  • Deep expertise in statistical modeling, machine learning, and predictive analytics.
  • Strong programming skills in Python, R, or similar languages.
  • Experience in deploying models in production environments.
  • Understanding of feature engineering and model validation techniques.

Responsibilities

  • Define and lead enterprise data science strategy for claims optimization and fraud detection.
  • Build and manage a high-performing team of data scientists and analysts.
  • Drive the development of predictive models for claims severity and risk management.
  • Oversee statistical modeling and advanced analytics from ideation to deployment.
  • Collaborate with AI Engineering to transition research models to production.
  • Establish modeling standards and validation protocols organization-wide.
  • Present data-driven insights and modeling outcomes to executive leadership.

Benefits

  • Work-life balance and growth opportunities.
  • Recognition as America's Greatest Workplaces by Newsweek.
  • A certified Great Place to Work culture.
  • Support from a caring organizational culture.
  • Commitment to diversity, equity, and inclusion.
Full Job Description
Job 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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About Sedgwick

Sedgwick is a global provider of insurance, risk management, and related services. The company was founded in 1969 and is headquartered in Boston, Massachusetts. Sedgwick offers a range of services to clients in various industries, including property and casualty insurance, workers' compensation, and disability management. The company has a team of experienced professionals who work closely with clients to develop customized solutions that meet their specific needs. Sedgwick has a reputation for delivering high-quality service and has been recognized for its excellence in the insurance industry.
Learn more about Sedgwick
Size
10,000 employees
Industry
Finance & Insurance
Founded
1969
* Ladders Estimates

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