PNC is looking to solve issues related to CECL reserve production and CCAR stress credit loss projection by hiring a Quantitative Analytics & Model Development Analyst.
Requirements
- Able to design and implement the process based on business requirements with the computer language (python is preferrable).
- Strong experience with Python
- Experience with Linux system
- Analyzes complex data and associated quantitative analysis.
- Uses quantitative tools and techniques to measure and analyze model risks and reaches conclusions on strengths and limitations of the model.
- Performs qualitative and quantitative assessments of all aspects of models including theoretical aspects, model design and implementation as well as data quality and integrity.
Responsibilities
- Able to design and implement the process based on business requirements with the computer language (python is preferrable).
- Able to identify, debug, solve issues independently
- Work with internal and external teams to understand business requirements, develop solutions, analyze outputs, and delivery results.
- Performs advanced quantitative analyses and models development to support decision-making by running quantitative strategies.
- Analyzes and develops new model frameworks by supporting the line of business.
- Refines, monitors, and reviews existing models.
- Works with large data to create models.
Other
- This position is primarily based in a PNC location. Responsibilities require time in the office or in the field on a regular basis.
- Detail-oriented and quick learner.
- Strong communication skills
- Knowledge on credit loss, CECL/CCAR, balance sheet products is preferred.
- PNC will not provide sponsorship for employment visas or participate in STEM OPT for this position.
