Quantitative Analytics & Model Analyst Senior - C&IB - Commercial

PNC•Pittsburgh, PA

1d•Onsite

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 Analyst Senior within PNC's Data Model Analytics organization, you will be based in Pittsburgh or Philadelphia, PA; Cleveland, OH; or Tyson's Corner, VA. 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.

Requirements

2–3+ years of professional experience in quantitative analytics, modeling, or a related role.
Strong Python programming and coding skills.
Solid foundation in mathematics and statistics.
Hands on experience with logistic regression and linear regression.
Experience applying machine learning techniques.
Proven experience developing and implementing models end to end.
Ability to build or demonstrate a portfolio of modeling or analytical work.
Bachelor’s degree in mathematics, Statistics, Quantitative Analytics, or a related quantitative field.
Strong presentation, communication, and documentation skills, with the ability to explain complex concepts clearly.
Roles at this level typically require a university / college degree, with 3+ years of relevant / direct industry experience.
In lieu of a degree, a comparable combination of education, job specific certification(s), and experience (including military service) may be considered.
Bachelors

Nice To Haves

Experience with PySpark or working in distributed data environments.
Banking or financial services experience.
Knowledge of credit risk or portfolio metrics such as PD (Probability of Default), LGD (Loss Given Default), and EAD/ED (Exposure at Default).
Analytical Thinking
Credit Risks
Data Analytics
Financial Analysis
Model Development
Operational Risks
Quantitative Models
Risk Appetite
Bank Quantitative Analysis
Consulting
Data Gathering and Reporting
Effective Communications
Predictive Analytics
Quantitative Techniques
Regulatory Environment - Financial Services
Testing
Certifications are often desired.

Responsibilities

Develop, implement, and maintain quantitative and machine learning models for analytics and decision support.
Apply statistical and mathematical techniques, including logistic and linear regression, to solve business problems.
Perform data analysis, feature engineering, model training, testing, and validation.
Use Python to write clean, efficient, and well documented code for modeling and analysis.
Evaluate model performance using appropriate metrics and ensure robustness and accuracy.
Prepare presentations and written documentation to clearly communicate model methodology, results, and insights to technical and non technical audiences.
Collaborate with cross functional partners to understand requirements and translate them into analytical solutions.
Support model lifecycle activities, including enhancements, recalibration, and monitoring.
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

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
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.