Data Scientist, Retail Banking Analytics

PNC Financial Services Group, Inc.; Cleveland (OH); Vor Ort; USD 86.000 - 173.000; Vollzeit

Zusammenfassung

PNC Financial Services Group, Inc. is seeking a Data Scientist in its Retail Banking ML & Predictive Modeling team, based in Pittsburgh, Cleveland, or Tyson's Corner. You will build and evaluate predictive models, run experiments, and translate complex results into actionable guidance for business leaders.

The role emphasizes large-scale data work, collaboration with risk, analytics, and product teams, and delivering data-driven insights to improve customer outcomes and credit risk decisions.

Qualifikationen

• Bachelor’s degree in a quantitative field; 2–3 years in data science or predictive analytics.
• Experience building and implementing predictive models using large datasets.
• Strong knowledge of statistical modeling and machine learning techniques; model evaluation.
• Experience with credit risk, retail banking, or customer analytics models.
• Proficiency in Python, R, or SAS; familiarity with PySpark/SQL.

Aufgaben

• Develops and evaluates predictive models for Retail Banking.
• Designs and analyzes experiments; optimizes data-driven strategies.
• Communicates insights to business leaders and executives; creates data storytelling outputs.
• Collaborates with Risk, Strategy, Analytics, and Business teams to implement models.
• Maintains and enhances production modeling frameworks.

Kenntnisse

Python

R

SAS

SQL

GitHub

Ausbildung

Bachelor’s Degree in Statistics, Mathematics, Data Science, Computer Science, Economics, Finance, Engineering, or related quantitative field

Master’s Degree (preferred)

Tools

Teradata

Hadoop

AWS

Impala

Hive

Trino

Oracle

MySQL

PostgreSQL

TOAD

Jobbeschreibung

PNC Financial Services Group, Inc. is seeking a Data Scientist in its Retail Banking ML & Predictive Modeling team, based in Pittsburgh, Cleveland, or Tyson's Corner. You will build and evaluate predictive models, run experiments, and translate complex results into actionable guidance for business leaders.

The role emphasizes large-scale data work, collaboration with risk, analytics, and product teams, and delivering data-driven insights to improve customer outcomes and credit risk decisions.