Portfolio Analytics & Strategy Specialist

$65,000 - $169,780/Yr

PNC - Dallas, TX

Part-time - Mid Level

Dallas, TX

Credit Intermediation and Related Activities

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 Portfolio Analytics & Strategy Specialist within PNC's Retail Lending Decision Science organization, you will use data and analytics to improve business results and customer outcomes. The candidate will have the opportunity to combine their knowledge of the consumer lending business, operational execution, and analytical techniques to craft actionable strategies that drive results in the default lifecycle. The ideal candidate will play a pivotal role in developing, implementing, and refining default strategies to optimize recovery rates, minimize losses, and enhance customer relationships. This role requires a deep understanding of data analytics, risk management, and strategic decision-making. This role will be based in Pittsburgh, Cleveland, Tysons Corner, Wilmington, Houston, Dallas, New York, Birmingham, Charlotte, Atlanta, Austin, or Chicago. The 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 the manager's discretion. In this role, you will perform strategic analysis by analyzing default trends, customer behavior, and economic factors to develop effective default management strategies. You will interpret data using advanced analytics tools and methodologies to interpret large datasets, identify patterns, and derive actionable insights. Additionally, you will assess risk associated with default scenarios, including credit risk, operational risk, and market risk, to inform strategic decision-making. You will design and implement innovative default management strategies tailored to specific customer segments, product lines, or market conditions. Collaboration is key, as you will work closely with cross-functional teams, including risk management, finance, operations, and legal departments, to ensure alignment and execution of default strategies. Monitoring performance will involve establishing key performance indicators (KPIs) and regularly monitoring the effectiveness of default strategies, making data-driven adjustments as necessary. You will also ensure compliance by staying abreast of industry regulations, best practices, and emerging trends related to default management to mitigate regulatory risks. Finally, you will communicate with stakeholders by presenting findings, recommendations, and progress updates to senior leadership, stakeholders, and regulatory bodies as required.

Responsibilities

• Analyze default trends, customer behavior, and economic factors to develop effective default management strategies.
• Utilize advanced analytics tools and methodologies to interpret large datasets, identify patterns, and derive actionable insights.
• Evaluate the risk associated with default scenarios, including credit risk, operational risk, and market risk, to inform strategic decision-making.
• Design and implement innovative default management strategies tailored to specific customer segments, product lines, or market conditions.
• Work closely with cross-functional teams, including risk management, finance, operations, and legal departments, to ensure alignment and execution of default strategies.
• Establish key performance indicators (KPIs) and regularly monitor the effectiveness of default strategies, making data-driven adjustments as necessary.
• Stay abreast of industry regulations, best practices, and emerging trends related to default management to ensure compliance and mitigate regulatory risks.
• Present findings, recommendations, and progress updates to senior leadership, stakeholders, and regulatory bodies as required.

Requirements

• Strong understanding of advanced data mining techniques, curating, processing, and transforming data to produce sound datasets.
• Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop.
• Experience in Machine Learning including Classification, Forecasting, Anomaly Detection, Pattern Detection, Text Mining, using a variety of techniques such as Decision trees, Time Series Analysis, Bagging and Boosting algorithms, Neural Networks, Deep Learning.
• Experience with analytical programming languages, tools, and libraries (Python ecosystem).
• Experience in SQL and relational databases.
• Experience in analyzing complex problems and translating them into an analytical approach.
• Experience with analytics applied to financial services or consumer lending.
• Strong leadership, stakeholder management, communication, partnership, and teamwork skills.
• Degree in an analytical field preferred (e.g., Computer Science, Data Science, Engineering, Applied Mathematics, Data Analysis, Statistics, Operations Research).
• Knowledge of Tableau helpful, but not required.

Nice-to-haves

• Knowledge of Tableau helpful, but not required.

Benefits

• 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
• Maternity and/or parental leave
• Up to 11 paid holidays each year
• 8 occasional absence days each year
• Between 15 to 25 vacation days each year, depending on career level and years of service.