Portfolio Analytics & Strategy Specialist (Fraud Model Analyst)

PNC Financial Services Group, Inc.; Denver (CO); On-site; USD 100,000 - 140,000; Full time

Job summary

PNC Financial Services Group, Inc. seeks a Portfolio Analytics & Strategy Specialist (Fraud Model Analyst) to join its Technology organization in multiple U.S. cities, including Denver, CO. The role focuses on developing, testing, and validating quantitative models to detect fraud and deter AML activities.

You will guide model users, coordinate with risk and audit partners, and mentor the modeling team while solving complex business problems with rigorous analytics.

Qualifications

• Experience with quantitative models and model validation.
• Proficiency in R or Python and handling large datasets.
• Knowledge of data analytics and statistical methods.

Responsibilities

• Oversees development, testing, and validation of quantitative models for fraud detection.
• Maintains communication with model users and stakeholders across functions.
• Leads evaluation of model risks and improvements to model controls.
• Coordinates with oversight, risk, audit, and regulatory partners on documentation.

Skills

Python

R Language

SQL

SAS

Statistical Modeling

Data Visualization

Tools

Tableau

Hadoop

Trillium

Job description

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 Portfolio Analytics & Strategy Specialist (Fraud Model Analyst) within PNC's Technology organization, you will be based in Cleveland/Strongsville OH, Pittsburgh PA, Birmingham AL, Dallas TX, Phoenix AZ or Denver CO

Requirements:

• Python, R Language, SQL, SAS nice to have
• Statistical Modeling, Validation
• Data Science, Statistics and Data Analytics
• Graph Database experience
• Data Correlation and Visualization

Job Description - Model Owner

• Oversees the development, testing, and validation of quantitative models (machine learning and statistical) used for detecting and deterring fraud. Conducts robust and comprehensive model testing, model monitoring, defect resolution, and analysis in accordance with model development lifecycle standards.
• Conducts ongoing communication and support for model users, including downstream model owners, and others who use the models for purposes of anti-money laundering, fraud detection and deterrence, and other uses.
• Directs complex qualitative and quantitative assessments of all aspects of models including theoretical aspects, model design and implementation as well as data quality and integrity. Confirms the reviews of complex reports including model documentation, model monitoring, QC findings, and model controls.
• Leads in evaluating identified model risks, defects, and issues, and reaches conclusions on strengths and limitations of the model. Works toward resolution and enhancement related to model shortcomings.
• Conducts ongoing communication with oversight, validation, risk management, internal audit, external audit, and regulatory compliance partners. This communication includes written responses to questions, formalized documentation of findings, and presentations to appropriate committees, working groups and other parties.
• Provides leadership, direction, and oversight to model developers who support the ongoing maintenance, management, and validation of the models.
• Provides coaching, training, direction, and best practices to the modeling team.
• Can manage the work-sets of multiple model developers in remote locations, including offshore.
• Solves business problems using a structured, analytically rigorous approach, and synthesize results for presentation to less technical audiences (model users and senior management)
• Solid understanding of probability, linear algebra and statistical modeling
• Proficiency with R or Python, and Hadoop, is required.
• Proficiency in SQL and working with large datasets is required.
• Proficiency with Trillium and/or Tableau is desirable but not required.
• Knowledge of data management is desired but not required.

PNC is an in-office company that fosters a supportive culture where employees can thrive and achieve balance.

PNC will not provide sponsorship for employment visas or participate in STEM OPT for this position.

Job Description

Provides financial and regulatory reporting and analyses to maintain adequate controls over the financial and regulatory reporting processes. Responsible for running complex business performance, risk and operational analytics. May include the development of analytical methods/models to assess market, credit and/or operational risk of new and existing financial products. Leverages business / product expertise to rigorously analyze large datasets, improve risk adjusted returns, deliver profitable growth, and communicate conclusions. Synthesizes analytical results and develops, recommends, and implements business strategies that improve lending decisions, assist in managing risk, increase revenues, reduce exposure to losses, meet business goals, and improve performance. Establishes baselines for strategies and tracks actual performance to expectations. Applies predictive models, third party data, and other tools to develop and execute appropriate segmentation and targeting for acquisition and portfolio strategies to provide insight into portfolio risk. Manages engagements with internal and external information suppliers ensuring solution is fit for purpose while maintaining appropriate governance and oversight. Works with business, credit, data, and model development partners to design, develop, and monitor test designs and analytical reporting to track and enhance strategies. Designs / enhances standard reporting suites for regular product / portfolio reviews. Collaborates with the line of business, Finance, and Risk partners to assess and establish credit risk appet