Model development expert - sheet
R200121
Job Profile 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 Expert within PNC's Balance Sheet Analytics & Modeling organization, you will sit in Pittsburgh or Philadelphia, PA, Cleveland, OH, Charlotte, NC, Wilmington, DE, New York City, Tysons, VA, Dallas or Houston, TX. 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. As a Quantitative Analytics & Model Development Expert 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 Anti-Money Laundering 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. 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
- Collaboration with 1st, 2nd and 3rd line of defenses and other key stakeholders
- Master’s or PhD degree in Statistics or Econometrics
- 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, SAS, 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
- Proven ability to lead and mentor other data scientists
- Ability to manage multiple projects simultaneously
- Strong teamwork skills and ability to work across different departments
- Experience in banking/ financial services
- Experience with anti-fraud and/or anti-money laundering modeling
- Hands-on experience building various types of AI/Machine Learning models, including neural networks
- Experience with cloud platforms like AWS, Google Cloud, or Azure
- Provides strategic and analytical insights around quantitative analyses, processes, and validations. Reviews complex quantitative analyses and models and engages with the Line of Business to enhance model development by incorporating business feedback.
- Oversees the development of new model frameworks by supporting the line of business and provides consultative feedback around improvements. Reviews any recommended changes to existing models. Conducts executive level communication during the course of the review.
- Performs the most complex qualitative and quantitative assessments on all aspects of models including theoretical aspects, model design and implementation as well as data quality and integrity. Reviews reports and associated quantitative analysis and provides analytical insight into potential areas of improvement. Reviews validation of existing models and assesses model risks.
- Reviews the evaluations of identified model risks and provides high level consultation around recommended conclusions on strengths and limitations of the model.
- Provides consultative feedback around the preparation and analysis of regulatory compliance documents.
- 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.
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