About The Position

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 within PNC's Balance Sheet Analytics & Modeling organization, you will be based in Pittsburgh or Philadelphia, PA, Cleveland, OH, Charlotte, NC or Tysons Corner, VA. As a Quantitative Analytics & Model Development Analyst within PNC's Anti-Money Laundering Analytics & Modeling team, you will be part of a cohesive team of professionals who utilize a variety of statistical techniques to build models to detect, monitor, and avert concerning patterns of account activity. In this role, you will work with key stakeholders across the bank 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. You will be leading innovative AML projects that are patentable, utilizing statistical techniques, including logistic regression, clustering, gradient boosting, neural network, and other machine learning algorithms, to design samples and build statistical models. 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.

Requirements

  • Successful candidates must demonstrate appropriate knowledge, skills, and abilities for a role.
  • Roles at this level typically require a university / college degree, with 3+ years of relevant / direct industry experience.

Nice To Haves

  • Master's degree or higher in a quantitative field
  • 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 productionizing 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 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

Responsibilities

  • 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
  • Experience in developing GenAI solutions
  • 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
  • Collaboration with 1st, 2nd and 3rd line of defenses and other key stakeholders
  • 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.

Benefits

  • PNC offers a comprehensive range of benefits to help meet your needs now and in the future.
  • Depending on your eligibility, options for full-time employees include: medical/prescription drug coverage (with a Health Savings Account feature), dental and vision options; employee and spouse/child life insurance; short and long-term disability protection; 401(k) with PNC match, pension and stock purchase plans; dependent care reimbursement account; back-up child/elder care; adoption, surrogacy, and doula reimbursement; educational assistance, including select programs fully paid; a robust wellness program with financial incentives.
  • In addition, PNC generally provides the following paid time off, depending on your eligibility: maternity and/or parental leave; up to 11 paid holidays each year; 9 occasional absence days each year, unless otherwise required by law; between 15 to 25 vacation days each year, depending on career level; and years of service.
  • To learn more about these and other programs, including benefits for full time and part-time employees, visit pncthrive.com.
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