Position Overview

At PNC, our people are our greatest differentiator and competitive advantage in the markets we serve. We are all united in delivering the best experience for our customers. We work together each day to foster an inclusive workplace culture where all of our employees feel respected, valued and have an opportunity to contribute to the company’s success. As a Quantitative Analytics & Model Development Analyst Senior within PNC's Balance Sheet Analytics & Modeling Anti-Money Laundering organization, Model Development Team, you will be based in Pittsburgh, PA or Birmingham, AL. This position is primarily based in a PNC location. Responsibilities require time in the office or in the field on a regular basis.


Role Overview:

You will utilize a variety of statistical techniques to generate analysis and build models to detect, monitor, and avert concerning patterns of account activity. You will work with key stakeholders to identify patterns and risk indicators within the firm’s account and transaction datasets, identify opportunities for new strategies, and recommend improvements to existing strategies.


Specific responsibilities for this role include (but are not limited to):

• Use a variety of analytical techniques to extract usable information from various data sources, including customer, account, and transactional data sets
• Participate in data set creation, analysis, reporting, model building, model monitoring and model documentation
• Effectively communicate analytical results, represent the modeling team in various forums to inform senior executives and various team partners of progress on key modeling efforts
• Work together within a team of analysts to validate each other’s work sets, code, and machine learning models
• Take on ad-hoc exercises to close gaps and identify suspicious activity within a fast-paced environment
• Collaboration with 1st, 2nd and 3rd line of defenses and other key stakeholders


Preferred skills and experience:

• Bachelors, Master’s or PhD degree in a quantitative field (e.g., Statistics, Mathematics, Economics, Computer Science, Engineering, Physics, Quantitative Psychology, Quantitative Political Science, MBA with a specialization in Analytics) with 3 year of relevant work experience
• Strong experience executing complex queries and building large datasets using SQL, PySpark, or other querying tools
• Experience designing samples and developing predictive models using regression, clustering, decision trees approaches, and using Machine Learning techniques/algorithms like gradient boosting, neural networks.
• Strong communication skills that encompass writing (experience writing documentation with regulatory requirements is a plus), communicating, facilitating, and presenting cogently to and/or for all levels of audiences
• A demonstrated history of successfully managing several projects concurrently
• A demonstrated ability to develop strong relationships and partnerships within and outside of the organization
• Understanding of statistics including sampling weights, confusion matrices, and confidence intervals
• Experience working in AWS for model development
• Experience writing documentation with regulatory requirements
• Experience analyzing code and conducting tests and analysis for quality assurance to confirm it is working as expected

PNC will not provide sponsorship for employment visas or participate in STEM OPT for this position.

Job Description

• Independently performs advanced quantitative analyses and model development to drive decision-making by running quantitative strategies. Makes recommendations based on analyses.
• Analyzes and develops new model frameworks by supporting the line of business. Refines, monitors, and reviews existing models. Conducts on-going communication with model owners and model developers during the course of the review. Works with larger, more complex datasets to create models.
• Performs quantitative analysis and develops complex reports. Performs qualitative and quantitative assessments of all aspects of models including theoretical aspects, model design and implementation as well as data quality and integrity. Analyzes complex data and associated quantitative analysis. Makes recommendations based on findings from data analytics.
• Uses quantitative tools and techniques to measure and analyze model risks and reaches conclusions on strengths and limitations of the model.
• Prepares and analyzes detailed documents for val