About The Position

As a Senior ML Engineer at Palms Insurance, you will architect AI and data engineering solutions that directly enhance underwriting profitability, claims accuracy, reinsurance optimization, and operational efficiency across our P&C portfolio. This strategic role requires deep expertise in insurance data ecosystems—policy administration, claims management, reinsurance structures (assumed and ceded), and insurance financial accounting—combined with advanced ML capabilities to address property risks, casualty exposures, and regulatory compliance challenges.

Requirements

  • Master's or Ph.D. in Physics, Mathematics, Computer Science, or related field
  • 7+ years in data engineering and ML with 5+ years in P&C insurance and 3+ years in reinsurance operations
  • 7+ years hands-on AWS experience (Glue, Redshift, S3, Lambda, CloudWatch)
  • Extensive knowledge of reinsurance treaty types: quota share, surplus share, excess of loss, stop loss, facultative, finite risk
  • Demonstrated expertise in reinsurance financial accounting: premium and loss ceding calculations, commission settlements (flat, sliding scale, profit commission), reinstatement premium accounting, experience refunds, loss portfolio transfers, and retroactive reinsurance.
  • Expertise in reinsurance accounting: premium/loss ceding, commission settlements, reinstatement premium, experience refunds, commutations
  • Strong database architecture, data warehousing, and ETL experience
  • Experience with Power BI, Grafana, and web app tools
  • Strong Scrum project management skills
  • Deep understanding of P&C insurance concepts: combined ratio mechanics, loss triangles, IBNR methodologies, cat modeling, treaty reinsurance structures, and regulatory reporting (Schedule P, Annual Statement)
  • Bachelor’s Degree
  • Experience: 4+ years

Nice To Haves

  • ARe/CRe (Reinsurance Fellowship/Chartership), or progress toward reinsurance credentials is highly desirable
  • CPA, CFA, or advanced coursework in insurance accounting and financial reporting is a strong plus
  • Insurance experience in Commercial or Specialty (Property & Casualty)
  • Master’s Degree
  • Doctoral Degree

Responsibilities

  • Build robust ETL/ELT pipelines using AWS (Glue, Redshift, S3, Lambda, Aurora) integrating P&C data including policy bordereaux, claims transactions, loss runs, exposure data, and reinsurance bordereaux
  • Implement data quality frameworks validating P&C metrics: loss ratios, combined ratios, reserve adequacy, IBNR estimates, exposure accumulation, ceded premium reconciliation, and sliding scale commission calculations
  • Design LLM-based ingestion workflows automating data mapping for MGAs, carriers, reinsurers, and program administrators
  • Create semantic layers translating raw data into standardized P&C schemas (ISO classifications, territory mappings, treaty types, attachment points)
  • Oversee production deployments with A/B testing frameworks for ML-driven underwriting and claims decisioning
  • Handle ad-hoc reporting, data anomaly resolution, and AWS job-aid refactoring
  • Develop automated reconciliation pipelines matching ceding company statements, reinsurer statements, and internal records with exception workflows
  • Build ML-driven anomaly detection identifying premium discrepancies, commission errors, and loss allocation mismatches
  • Create predictive cash flow models for reinsurance recoverable forecasting collection timing and dispute impacts
  • Implement actuarial support for Schedule F preparation, collectability assessments, unauthorized reinsurer collateral tracking, and NAIC regulatory reporting
  • Engineer financial pipelines supporting SAP and GAAP requirements including DAC, UPR, loss reserve discounting, and contingent commission accruals
  • Co-develop data strategy with the VP of Data Analytics & Technology aligned with actuarial, underwriting, claims, and finance objectives
  • Implement data governance standards ensuring compliance with state insurance regulations, NAIC reporting requirements, Solvency II (for international operations), credit for reinsurance regulations, and SOC 2 controls
  • Maintain CI/CD processes via GitHub with peer review protocols, comprehensive code documentation, and model validation frameworks meeting actuarial and reinsurance accounting standards
  • Lead peer-review processes to ensure high-quality and reliable data science work.
  • Develops machine learning, optimization and other modeling solutions
  • Prepares comprehensive documented observations, analyses and interpretations of results including technical reports, summaries, protocols and quantitative analyses
  • Works with big data and distributed computing platforms
  • Develops software and contributes to product development
  • Performs other job-related duties as assigned

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What This Job Offers

Job Type

Full-time

Career Level

Mid Level

Number of Employees

5,001-10,000 employees

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