FM is looking to solve property risk management and resilience problems for its policyholder-owners by using data science and analytics to prevent property loss and make cost-effective risk management decisions.
Requirements
- Advanced Knowledge and Working Experience in Generalized Linear Models (Logistic Regression, Zero-Inflated Model, etc.)
- Model Regularization
- Probability Distributions
- Hypothesis testing
- Statistical Inference
- Machine Learning (Random Forest, Clustering, Gradient Descent, Gradient Boosting, etc.)
- Simulation
Responsibilities
- Translating business needs into analytics
- Interpretation of analytics into business applications
- Developing and applying statistics, artificial intelligence, machine learning, and deep learning to various business problems in loss prevention
- Planning, conducting, and advising the development and evaluation of real-world, large-scale problems using artificial intelligence/machine learning
- Using statistics to advance the mission and goals of FM
- Developing and applying machine learning models such as Random Forest, Clustering, Gradient Descent, Gradient Boosting, etc.
- Working with cloud data analytics platforms such as Databricks
Other
- Ph.D. in Statistics, Biostatistics or Operational Research with 2+ years of industry experience or a Master's degree with 5+ years of industry working experience in data science modelling
- 5+ years of experience of data processing, statistical analysis and modelling
- 2+ years of experience of working with cloud data analytics platform
- Experience as the lead role of full-cycle data science projects
- Working experience in risk management and/or property insurance is strongly preferred
