Data Scientist - Retail Banking; ML & Predictive Modeling

Position: Data Scientist - Retail Banking (ML & Predictive Modeling)
PA - Pittsburgh (15222)

VA - Tysons Corner

OH - Cleveland (44114)

Full time

R234750

** Position Overview*
* 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 Data Scientist within PNC's Retail Banking (ML & Predictive Modeling) organization, you will be based in Pittsburgh, PA;
Cleveland, OH;
Tyson's Corner, VA.

Job Summary:

We are seeking a highly analytical and technically skilled Data Scientist to support the development, evaluation, implementation, and optimization of advanced predictive models within Retail Banking. This role will focus on building machine learning and statistical models, designing and analyzing experiments, enhancing data-driven business strategies, and communicating actionable insights to business leaders and executive stakeholders.

The ideal candidate combines strong predictive modeling expertise with hands-on experience working with large-scale data environments and modern programming languages. This position offers the opportunity to expand existing production modeling frameworks while partnering closely with risk, strategy, analytics, and business teams.

Required Qualifications:

- Bachelor's Degree in Statistics, Mathematics, Data Science, Computer Science, Economics, Finance, Engineering, or a related quantitative field.

- 2-3 years of professional experience in data science, predictive analytics, statistical modeling, machine learning, or quantitative analysis.

- Experience developing and implementing predictive models using large datasets.

- Strong understanding of statistical modeling, machine learning techniques, and model performance evaluation.

- Experience building and validating credit risk, retail banking, or customer analytics models.

- Proficiency in one or more of the following programming languages:
Python, R, or SAS

- Experience with :
PySpark, R Shiny, or SQL

- Experience working with large-scale data environments and big data technologies, including Teradata, Hadoop, AWS, Impala, Hive, or Trino

- Experience with relational database platforms such as:
Oracle, MySQL, PostgreSQL, TOAD

- Experience using Git Hub or other version control platforms.

- Strong communication and presentation skills with the ability to translate technical findings for non-technical audiences.

Preferred Qualifications:

- Master's Degree in a quantitative discipline.

- Experience supporting Retail Banking, Consumer Banking, Risk Management, Credit Risk, or other Financial Services functions.

- Experience with model governance, model risk management, and regulatory expectations within the banking industry.

- Prior experience supporting EAD, PD, LGD, CECL, stress testing, or other risk modeling frameworks.

- Knowledge of model deployment, model monitoring, and production support processes.

- Experience working in Agile or cross-functional analytics environments.

- Demonstrated ability to influence business decisions through advanced analytics and data storytelling.

- Experience presenting analytical results to senior leadership and executive stakeholders.

PNC is an in-office company that fosters a supportive culture where employees can thrive and achieve balance. We encourage candidates to connect with their recruiter and hiring manager to understand workplace expectations and ensure the role aligns with their goals.

PNC will not provide sponsorship for employment visas or participate in STEM OPT for this position.

** Job Description*
* + Performs analytical tasks on vast amounts of structured and…