Associate Data Scientist - Corporate & Institutional Banking
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 Associate Data Scientist within PNC's Corporate & Institutional Banking organization, you will be based in Pittsburgh, or Philadelphia, PA; Cleveland, OH; Birmingham, AL; Houston, TX; or Charlotte, NC. PNC is seeking an Associate Data Scientist to join the Corporate and Institutional Banking (C&IB) team. In this role, you will partner with senior data scientists, business stakeholders, and engineering teams to explore data, perform analysis, and support the development and delivery of analytical solutions to address business problems and support C&IB growth objectives. The team’s work spans key business verticals including Sales, Credit and Underwriting, and Operations, providing opportunities to build foundational experience applying analytics across the full lifecycle of client engagement and operational decision-making. The ideal candidate has strong analytical problem-solving skills, foundational experience in data analysis and machine learning, and is eager to learn how to translate business needs into scalable analytical solutions under guidance.
Requirements
- 1-2 years of relevant professional experience in data science, analytics, or a related field (including internships/co-ops), or equivalent academic experience.
- Proficiency in Python or R.
- Strong SQL skills and experience working with large datasets.
- Exposure to big data tools (e.g. Spark).
- Familiarity with Git or version control concepts.
- Foundational understanding of machine learning concepts, including feature engineering and basic model evaluation.
- Exposure to Generative AI concepts and tools.
- Exposure to delivery artifacts such as business requirements, user stories, or test cases.
- Experience supporting testing or validation of analytical solutions.
- Ability to design and develop dashboards to communicate, visualize, and monitor analytical results using Python or R–based frameworks (e.g. R Shiny, Dash, Flask)
- Customer Focused - Knowledgeable of the values and practices that align customer needs and satisfaction as primary considerations in all business decisions and able to leverage that information in creating customized customer solutions.
- Managing Risk - Assessing and effectively managing all of the risks associated with their business objectives and activities to ensure they adhere to and support PNC's Enterprise Risk Management Framework.
- Analytical Thinking
- Data Analytics
- Data Mining
- Data Science
- Machine Learning (ML)
- Data Architecture
- Data Mining
- Disruptive Innovation
- Information Capture
- Machine Learning
- Modeling: Data, Process, Events, Objects
- Prototyping
- Query and Database Access Tools
- Bachelor's degree in a quantitative field (Computer Science, Data Science, Machine Learning, Mathematics, Statistics)
Nice To Haves
- Exposure to business domains such as credit, accounting, or financial operations.
- Familiarity with underwriting concepts or a willingness to learn them on the job.
- Interest in working across multiple business areas
Responsibilities
- Use Python or R to explore data, perform analysis, and contribute to prototyping analytical approaches within established workflows.
- Support the development, validation, and monitoring of interpretable machine learning models using sound statistical and modeling techniques.
- Contributes to the delivery of analytical solutions from prototype through testing and deployment, working closely with senior team members and engineering partners.
- Support communication across business, product, and engineering teams by helping gather requirements and clearly explain analytical work and results.
- Assist in defining and tracking performance metrics to measure solution effectiveness.
- Actively learn and adopt best practices in model development, code quality, and production deployment.
- Supports the team with analytical tasks on vast amounts of structured and unstructured data to extract actionable business insights.
- Participates in the data gathering, data processing and data mining of large and complex datasets.
- Supports the team in developing algorithms using advanced mathematical and statistical techniques like machine learning to predict business outcomes.
- Assists with analytical experiments in a methodical manner to find opportunities for product and process optimization.
- Assists in the presentation of business insights to management using visualization technologies and data storytelling.
- May partner with Data Architects, Data Analysts, Data Engineers and Visualization Experts to develop data-driven solutions for the business.
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
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
