Risk Analytics Models
Skills
Computer ScienceData AnalysisData AnalyticsData ScienceDatasetsMathematicsPredictive Analytics
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 5+ years of statistical modeling experience with a Master’s or PhD degree in Statistics Mathematics Economics Engineering Computer Science or a quantitative field
- Proficient in Python SQL & Tableau
- Experienced in model development and data analysis
- Excellent knowledge of data science statistical methodologies and machine learning models e.g. linear regression logistic regression decision trees gradient boosting random forests neural network clustering analysis etc.
- Hands-on knowledge on common loss forecasting methodologies e.g. econometrics modeling discrete survival modeling state transition Markov Chain etc.
- Strong communications and presentation skills
- Someone who is highly motivated and drives change is eager to learn and able to work collaboratively in a complex and fluid environment
Nice to have
- Familiarity working with bureau sandbox data a plus
- Experience with generating credit reporting dashboard a plus
- Experience with developing and productionizing models in the AWS environment a plus
Day to day
- Developing quantitative/machine learning models to forecast product losses
- Aggregating and synthesizing datasets from multiple data environments
- Analyzing complex datasets to understand the performance and drivers for losses across various products
- Investigating external credit data to identify trends in the market and industry
- Conducting loss sensitivity analysis
- Automating models and analytical dashboards
- Monitoring the models’ performance and re-calibrating the models as needed
- Working with Business Units, Operations, Product, Capital Markets, Finance, Accounting and Risk partners