Quantitative Analytics & Model Consultant Senior - Data, Modeling & Analytics

Position Overview

Quantitative Analytics & Model Consultant Senior in PNC's Anti-Money Laundering Analytics & Modeling team. Based in multiple locations:
Pittsburgh, PA;
Philadelphia, PA;
Cleveland, OH;
Charlotte, NC;
Wilmington, DE;
Austin, TX;
Washington, DC; or Tysons Corner, VA.

At PNC, our people are our greatest differentiator and competitive advantage in the markets we serve. We foster an inclusive workplace culture where all employees are respected, valued, and have opportunities to contribute to the company's success.

Part of a cohesive team who use statistical techniques to build models that detect, monitor, and avert concerning patterns in account activity. Work with key stakeholders across the bank to identify patterns and risk indicators, propose new strategies, and recommend improvements to existing strategies. Lead innovative AML projects that are patentable, utilizing logistic regression, clustering, gradient boosting, neural network, and other machine learning algorithms to design experiments and build statistical models.

• Use a variety of analytical techniques to extract usable information from various data sources, including customer, account, and transactional datasets.
• Participate in data set creation, analysis, reporting, model building, model monitoring and model documentation.
• Effectively communicate analytical results and represent the modeling team in various forums to inform senior executives and partners about progress on key modeling efforts.
• Collaborate with 1st, 2nd, and 3rd line of defenses and other key stakeholders.

• Independently performs the most complex quantitative analyses and model development to support decision‑making by running quantitative strategies.
• Develops new model frameworks by supporting the line of business. Refines, monitors, and validates existing models. Conducts ongoing communication with model owners and developers during the review. Works with large data to create models.
• Performs the most complex qualitative and quantitative assessments on all aspects of models including theoretical aspects, design, implementation as well as data quality and integrity. Reviews reports and associated quantitative analysis. Validates existing models and assesses model risks.
• Evaluates identified 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.

• Master's degree or higher in a quantitative field.
• Experience in developing GenAI solutions.
• Experience with data mining, and data preparation for ML models including EDA, data transformations and preprocessing.
• Proficiency in statistical methods and tools, including experimental design, probability theory, and sampling.
• Expertise in building, scaling, and optimizing machine learning systems with industry recognized ML frameworks and algorithms.
• Strong programming skills in Python, PySpark, R, and/or SQL.
• Familiarity with big data technologies like Hadoop, Spark, Hive, Impala, etc.
• Experience working with model risk governing bodies in model validation, and with model implementation partners in product ionizing a model.
• Critical thinking and problem‑solving aptitude with the ability to apply analytical rigor to complex business problems.
• Ability to present complex technical concepts clearly and effectively to non‑technical stakeholders and business partners.
• Ability to manage multiple projects simultaneously.
• Strong teamwork skills and ability to work across different departments.

• Master's degree in Statistics, Mathematics, Engineering or Econometrics.
• Experience in banking/financial services.
• Experience with anti‑fraud and/or anti‑money laundering modeling.
• Hands‑on experience building various types of AI/ML models, including neural networks.
• Experience with cloud platforms like AWS, Google Cloud, or Azure.

Successful candidates must demonstrate appropriate knowledge, skills, and abilities for the role. Listed below are skills, competencies, work…