Data Scientist Senior - Internal Audit

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 Senior within PNC's Internal Audit organization, you will be based in Cleveland, OH; Pittsburgh, PA; Raleigh, NC or Birmingham, AL.

PNC's Internal Audit organization is seeking a highly motivated Senior Data Scientist to join a dynamic team that is redefining how risk is identified, monitored, and assessed across the enterprise. PNC's Internal Audit department is composed of industry leaders who provide independent, objective assurance and consulting services designed to add value and improve organizational performance. Through innovative use of data, emerging technologies, and analytical methodologies, the team is evolving audit practices to deliver deeper insights, proactive risk identification, and more effective assurance.

As a Senior Data Scientist, you will play a key role in delivering advanced analytical solutions that enhance audit effectiveness, improve operational insights, and support strategic decision-making across Internal Audit. You will collaborate with audit professionals, business partners, and technology teams to develop scalable, production-ready analytics and AI-enabled solutions that help identify risk and drive value.

The successful candidate will be a technically strong and innovative data scientist who can combine advanced analytical techniques with business acumen to solve complex risk challenges. This individual will help Internal Audit move beyond descriptive reporting toward predictive and AI-enabled insights that improve audit quality, strengthen risk identification, and drive strategic value across the organization.

Key Responsibilities

• Lead the design, development, testing, deployment, and maintenance of advanced analytics, machine learning, and AI-enabled solutions supporting Internal Audit priorities.
• Partner with audit teams and stakeholders to translate business challenges, audit objectives, and risk considerations into analytical solutions and data products.
• Develop predictive, diagnostic, anomaly detection, and risk-focused models that improve audit planning, testing, continuous monitoring, and reporting capabilities.
• Build scalable, maintainable, and reusable analytical frameworks, workflows, and data products that drive efficiency and insight generation across the audit lifecycle.
• Identify opportunities to leverage automation, machine learning, and generative AI technologies to enhance audit processes and risk identification.
• Collaborate with technology, data, and enterprise partners to support model deployment, productionization, data pipeline development, and ongoing solution maintenance.
• Ensure analytical solutions comply with established governance, validation, testing, documentation, and lifecycle management standards.
• Communicate analytical results and strategic recommendations to both technical and non-technical audiences, translating complex findings into actionable business insights.
• Mentor and provide technical guidance to team members while promoting best practices in data science, machine learning, software development, and analytics engineering.
• Contribute to the evolution of Internal Audit's data science, automation, and AI capabilities through innovation, thought leadership, and continuous improvement initiatives.

Desired Skills & Experience

Technical Skills

• Advanced proficiency in Python and SQL.
• Experience with data manipulation and analytical libraries such as Pandas, NumPy, Scikit-learn, PySpark, TensorFlow, or similar technologies.
• Experience working with large-scale data environments, including Hadoop-based platforms, distributed data processing frameworks, and enterprise data ecosystems.
• Experience using GitHub or other source control platforms for code management, collaboration, version control, and code review.
• Experience with machine learning, statistical modeling, predictive analytics, and data science methodologies.
• Experience with natural language processing (NLP), text analytics, document intelligence, topic modeling, and analysis of unstructured data.
• Experience developing, validating, deploying, and monitoring production analytics or machine learning solutions.
• Familiarity with software package, dependency, and artifact management tools such as Artifactory, Conda, pip, or similar enterprise development technologies.
• Familiarity with data visualization platforms such as Power BI, Tableau, or similar tools.

Emerging Technology Skills

• Experience with generative AI, large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG), AI agents, or related technologies preferred.
• Understanding of AI governance, model risk management, and responsible AI practices preferred.

Leadership & Business Skills

• Strong problem-solving and critical-thinking capabilities.
• Ability to influence stakeholders and communicate effectively across technical and business audiences.
• Demonstrated ability to manage multiple priorities and deliver high-quality solutions in a dynamic environment.
• Strong collaboration skills and a passion for mentoring and developing others.

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

• Leads the implementation of analytical projects that leverage vast amounts of structured and unstructured data to extract actionable business insights.

• Directs the data gathering, data processing and data mining of large and complex datasets.

• Leads the development of algorithms using advanced mathematical and statistical techniques like machine learning to predict business outcomes and recommend optimal actions to management.

• Leads analytical experiments in a methodical manner to find opportunities for product and process optimization. Presents business insights to management using visualization technologies and data storytelling.

• Partners with Data Architects, Data Analysts, Data Engineers and Visualization Experts to develop data-driven solutions for the business.

PNC Employees take pride in our reputation and to continue building upon that we expect our employees to be:

• 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.

Qualifications

Successful candidates must demonstrate appropriate knowledge, skills, and abilities for a role. Listed below are skills, competencies, work experience, education, and required certifications/licensures needed to be successful in this position.

Preferred Skills

Analytical Thinking, Competitive Advantages, Data Analytics, Data Mining, Data Science, Machine Learning (ML)

Competencies

Data Architecture, Data Mining, Disruptive Innovation, Information Capture, Machine Learning, Modeling: Data, Process, Events, Objects, Prototyping, Query and Database Access Tools

Work Experience

Roles at this level typically require a university / college degree, with 5+ years of industry-relevant experience. Specific certifications are often required. In lieu of