Associate Data Scientist - Corporate & Institutional Banking

PNC

Quick summary

Work type
On-site
Location
Pittsburgh, PABirmingham, ALCharlotte, NCHouston, TXPhiladelphia, PA
Salary
$75,000–$150,000 / yr
Posted
3 days ago

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $163k
This role $112k
$59k most similar roles pay here $225k

This role pays less than 98% of similar roles. Most pay $126,800–$199,800 — the shaded band above. At the midpoint, this role pays about $112k versus about $163k for comparable roles.

Based on 240 similar postings.

Employer

About PNC

PNC is one of the largest diversified financial services institutions in the U.S., based in Pittsburgh, PA, it provides retail banking, corporate banking, and asset management.

PNC currently has 172 open roles on FindRole.

Listed pay typically runs $86,250–$185,150 across 59 roles with salary data.

Most-posted roles

View all roles at PNC

At a glance

TL;DR · Associate Data Scientist - Corporate & Institutional Banking

PNC's Corporate & Institutional Banking team in Pittsburgh and other locations seeks an Associate Data Scientist to collaborate with senior data scientists, business stakeholders, and engineering teams on analytical solutions. This role involves using Python or R for data exploration and analysis, contributing to the development of interpretable machine learning models, and supporting their deployment across sales, credit, underwriting, and operations verticals. The candidate will also assist in defining performance metrics and communicating results effectively through dashboards built with frameworks like Shiny or Dash. Required skills include proficiency in Python or R, strong SQL abilities, experience with big data tools such as Spark, and foundational knowledge of machine learning concepts. Exposure to generative AI is preferred, along with an interest in financial operations and underwriting concepts.

What you'll do

  • Use Python or R to explore data and perform analysis.
  • Develop and validate interpretable machine learning models using sound statistical techniques.
  • Contribute to the delivery of analytical solutions from prototype through deployment.
  • Define and track performance metrics for solution effectiveness.
  • Assist in gathering requirements and explaining analytical work across teams.

What we're looking for

  • 1-2 years of relevant professional experience in data science or analytics.
  • Proficiency in Python or R and strong SQL skills.
  • Experience working with large datasets and big data tools like Spark.
  • Foundational understanding of machine learning concepts, including feature engineering.
  • Exposure to generative AI concepts and tools.
  • Ability to design and develop dashboards using frameworks like R Shiny or Dash.

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