Markel Service-posted 6 days ago
Full-time • Entry Level
Glen Allen, VA
Insurance Carriers and Related Activities

As part of the US & Bermuda Data & Analytics team, you will enable a specialty lines insurer to improve their portfolio performance and growth through analytics, reporting, and data driven insights. Our team is embedded within the lines of business that we support, helping to facilitate collaboration and meaningful partnerships. The primary function of this position is to support statistical modeling, portfolio analytics, and reporting. You'll put invaluable data tools into the hands of Markel decision makers, integrated directly into their systems and workflows. You'll work with a team of innovative experts in their respective disciplines: Data Scientists, Software Engineers, Actuaries, Data Engineers, and Business Intelligence Analysts.

  • Collaborate with business users, data scientists, engineers, and report analysts to translate requirements into scalable reporting and model solutions
  • Support machine learning operations (ML Ops) by deploying, monitoring, and maintaining models in production
  • Build and manage CI/CD pipelines for reporting, analytics, and ML workloads
  • Participate in code review, design discussion, and sprint planning within an agile framework
  • Collaborate with IT and Systems teams to integrate data solutions into underwriting systems and portals
  • Monitor system performance, identify bottlenecks, and implement improvements for scalability and reliability
  • Document processes, workflows, and best practices for transparency and knowledge sharing
  • Partner with DevOps and IT to ensure security, compliance, and governance of data systems
  • Stay current with emerging technologies and tools in data engineering, analytics, and ML Ops, recommending improvements when appropriate
  • Bachelor's degree in computer science, engineering, Data Science, or related field (or equivalent work experience)
  • Proven experience in ML Ops roles required
  • Experience in data engineering, analytics engineering, or experience with ML Ops tools and frameworks (MLflow, Azure ML, etc.)
  • Demonstrated experience with model deployment and serving through endpoints (e.g., Azure ML endpoints, etc.)
  • Solid programming experience (Python required, R also valuable)
  • Hands-on experience with cloud platforms (Azure strongly preferred; AWS/GCP also valuable)
  • Familiarity with data warehouses / lakehouses, (Databricks strongly preferred)
  • Comfort with statistical methods, predictive modeling, or machine learning deployment
  • Experience with CI/CD pipelines for analytics or ML deployments
  • Understanding of data modeling, relational databases, and schema design for analytics/reporting
  • Proficiency in SQL (query optimization, stored procedures, performance tuning)
  • Knowledge of version control systems (e.g., Git) and collaborative development practices
  • Knowledge of security, compliance, and access controls within data environments
  • Ability to work in an agile, collaborative environment with cross-functional teams
  • Strong analytical and problem-solving skills with the ability to troubleshoot complex issues
  • Ability to communicate technical concepts clearly with non-technical stakeholders
  • Exposure to reporting & visualization tools (Power BI, Tableau, Qlik, etc.)
  • Insurance and/or finance industry knowledge
  • Multiple health, dental and vision insurance plan options
  • Optional life, disability, and AD&D insurance
  • 401(k) with employer match contributions
  • Employee Stock Purchase Plan
  • PTO, corporate holidays and floating holidays
  • Parental leave
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