Senior Quant Analytics & ML Model Consultant

PNC Financial Services Group, Inc.; Pittsburgh (Allegheny County); Sur place; USD 112 000 - 250 000; Plein temps

Avantages offerts par ce poste

Health insurance

401(k) with company match

Paid holidays

Résumé du poste

PNC Financial Services Group, Inc. in Pittsburgh, PA is seeking a Senior Quantitative Analytics & Model Consultant to join the Retail Banking ML & Predictive Modeling team.

The role focuses on developing, validating, implementing, and enhancing advanced machine learning and quantitative models that support deposits, transactions, wealth management, customer segmentation, and retail banking initiatives. The position leverages large-scale data, cloud technologies, and experimentation to build and

Qualifications

• 8+ years in quantitative analytics, predictive modeling, or related field.
• Advanced Python and PySpark programming.
• Experience with cloud platforms (AWS/Azure/GCP).
• Advanced SQL with complex joins, aggregations, subqueries, and data transformation.

Responsabilités

• Perform the most complex quantitative analyses and model development to support decision-making.
• Develop new model frameworks and refine/validate existing models.
• Assess model risks and ensure data quality and integrity across large datasets.
• Prepare detailed validation/regulatory documentation.

Connaissances

Python

PySpark

Cloud computing

SQL

Big data

Analytical thinking

Communication to technical/non-technic

Cross-functional collaboration

Decision support through data

Formation

Bachelor's degree

Master's degree

PhD

Outils

AWS

Azure

GCP

Description du poste

PNC Financial Services Group, Inc. in Pittsburgh, PA is seeking a Senior Quantitative Analytics & Model Consultant to join the Retail Banking ML & Predictive Modeling team.

The role focuses on developing, validating, implementing, and enhancing advanced machine learning and quantitative models that support deposits, transactions, wealth management, customer segmentation, and retail banking initiatives. The position leverages large-scale data, cloud technologies, and experimentation to build and