AI/ML Engineer

Responsibilities
Key Requirements

Strong hands-on expertise in AI/ML, Data Science, Python, SQL, and Git/GitHub.
Proven experience building end-to-end data science and predictive modeling solutions, from problem definition through deployment.
Strong understanding of Property & Casualty (P&C) Insurance business processes.
Ability to translate complex business challenges into practical AI/ML and analytical solutions.
Strong focus on business outcomes and measurable impact, beyond model development.
Experience applying AI/ML solutions in areas such as:
Pricing
Risk Segmentation
Underwriting Decision Support
Forecasting
Operational Optimization
Strong GitHub and software engineering practices including:
Version Control
Code Reviews
Documentation
Testing
Reusable Code Development
Excellent communication skills with the ability to present technical concepts to business and non-technical stakeholders.
Ability to work as a senior independent contributor, driving initiatives end-to-end with minimal support.
Experience leading:
Business Discovery
Data Assessment
Model Development & Validation
Deployment

Qualifications
Bachelor's in Computer science, engineering or any related field