Risk Analytics & Modeling Manager

Key Skills

Data Modeling, Effective communication skills, Finance, Machine learning techniques, Presentation skills, Python Programming, R Programming, Risk Analytics, SAS, Statistics

Job Description

YOUR ROLE

We’re seeking a high energy, creative, and resourceful Risk Modeling Manager to provide thoughtful insights and expertise in developing, interpreting, and maintaining statistical and machine learning models. These model results enable Enact in its targeted acquisition, management, and distribution of risk and are foundational to the pricing, forecasting, economic capital assessment, and stress testing functions within the Business. This is a collaborative role that invites sharing expertise and ideas across business functions and directly contributes to the success of Enact.

YOUR RESPONSIBILITIES

• Build, update, and improve upon the forecasting accuracy of behavioral mortgage models - probability of default, loss given default, and policy lapse
• Construct and interpret machine learning models to provide insights and answer stakeholder’s questions
• Create stochastic modeling frameworks based on a variety of economic paths and analyze their probability distributions
• Provide scenario analysis, sensitivity analysis, what-if analysis, and other types of analysis as required
• Summarize and communicate your analysis of modeled cashflows to both technical and non-technical stakeholders
• Research industry standard techniques and innovative new approaches in order to improve all types of risk models
• Conduct thorough testing and validation on the IT implementation of modeled results
• Write technical documentation that compares models using a champion/challenger framework
• Collaborate with various stakeholders including teams in Risk, Finance, Pricing, IT, Commercial, and Loss Mitigation to promote understanding of risk models and their results

YOUR QUALIFICATIONS

• 4+ years of relevant work experience in building models based on economic or financial data
• Master's Degree in a quantitative discipline such as Statistics, Mathematics, Quantitative Finance, Economics, Data Science, or Actuarial Sciences
• Proficiency in a programming language such as Python, R, or SAS
• Thorough understanding of and demonstrated experience with statistical methodologies including least squares, logistic regression, and time-series forecasting such as GARCH
• Thorough understanding of and demonstrated experience with machine learning methodologies including random forest, gradient boosted trees, and k-means clustering
• Experience working with large, complex data sets including cross-sectional and time-series data
• Ability to analyze large volumes of data, draw conclusions, and independently present findings
• Analytical, data-based approach to exploration, modeling of data, and testing of hypothesis
• Ability to build and implement a project plan of model development life cycle including testing, validation, documentation, and monitoring the model performance
• Strong interest in learning the business details of mortgage insurance and various aspects of the mortgage and housing industry
• Strong communication, presentation, and collaboration skills that allows you to present findings with all levels within the organization
• Ability to take complete ownership of projects in a performance and results oriented environment

ADDITIONAL QUALIFICATIONS

• Either a Ph.D. in Statistics or a comparable quantitative field or additional work experience using mortgage data and machine learning 
• Experience in transition rate modeling at loan level using competing risk framework
• Experience with credit bureau data