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 Machine Learning Analyst Sr. within PNC's AML and Independent Risk Management organization, you can be based in Pittsburgh, PA, Cleveland, OH, Columbus, OH, Cincinnati, OH, Chicago, IL, Birmingham, AL, Washington DC, or New York City, NY.

This position is primarily based in a PNC location. Responsibilities require time in the office or in the field on a regular basis. Some responsibilities may be performed remotely, at manager’s discretion.

PNC is one of the largest diversified financial services institutions in the United States. At PNC we lean in to being Brilliantly Boring, and what could be more Brilliantly Boring than Anti-Money Laundering (AML)? The AML Data Science Solutions team is responsible for overseeing the use of artificial intelligence (AI) / machine learning (ML) to identify potentially suspicious behavior and assist sanctions enforcement. Collaborating with model developers and business users, our team takes a holistic view of our ML ecosystem. We aim to leverage the latest research in reliable and trustworthy machine learning to build a strong program that stands on strong evidence.

The successful candidate will work on a variety of challenges aimed at all parts of the MLOps cycle. Expect to help the team test out the latest science to assess its utility, explore avenues for boosting detectability, and develop approaches for improving overall observability and explainability of existing models. This role is particularly suited to candidates with an analytic background who are motivated to work on societally important business problems.

Preferred qualifications:

· Master’s Degree or above in data science, mathematics, computer science, or similar field
· Experience in AI / ML model assessment, testing, or validation
· Fluency in SQL and Python + scikit-learn. Experience with PyTorch, Pyro, and/or other AI/ML/data science languages and libraries is a plus.

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 validation and regulatory compliance, using applicable templates.

PNC Employees take pride in our reputation and to continue building upon that we expect our employees to be:

• Customer Focused - Knowledgeable of the values and practices that align customer needs and satisfaction as primary considerations in all business decisions and able to leverage that information in creating customized customer solutions.
• Managing Risk - Assessing and effectively managing all of the risks associated with their business objectives and activities to ensure they adhere to and support PNC's Enterprise Risk Management Framework.

Qualifications

Successful candidates must demonstrate appropriate knowledge, skills, and abilities for a role. Listed below are skills, competencies, work experience, education, and required