Work

  • Technical lead of the Actuarial Business Review
    • Generating business insights for over 50 reserving segments for senior and board management
    • Monitoring key KPIs like Actual vs Expected, Incurred and Premium Trackers, benchmarking Plan figures, attritional/large loss split and more
    • Fully automated pipeline that creates beautiful dash-inspired dashboards
  • AI in Reserving: Building an AI agent with SKILL.md to
    • Conduct actuarial analyses using reserving-studio and chainladder-python
    • Interact with databases by generating SQL queries from a curated SQL knowledge repository
    • Generate reports and artifacts for internal knowledge management and stakeholder communication
  • Custom Python-based ResQ API to easily pull and process reserving data
  • Attritional/large-loss splitting approach for reserving
    • Finding optimal large-loss threshold
    • Attritional reserving using chainladder-python
    • Large-loss projections based on frequency-severity analysis using GLMs and Monte Carlo simulations
  • Coordinating resegmentation of reserving segments
    • Building an automated mapping approach that reflects the new business logic
    • Building new analysis tools within python and chainladder-python to support mapping decisions

Personal

  • reserving-studio
  • AI-assisted math tutoring
    • Agentic approach using opencode alongside latex and markdown (Obsidian) to create student-tailored lessons and exercises
    • (Not yet open source)
  • Sharpen-the-saw projects
    • Learning [[Colemak]]