Data Scientist

Join PNC and help strengthen fraud mitigation with data science work focused on detecting emerging patterns. This onsite Data Scientist role sits within PNC’s Enterprise Fraud Organization (EFO) Monitoring React Identify team, where you will build and apply analytics to improve anomaly detection and uncover gaps that may impact business outcomes. The role is based in Pittsburgh, PA, Cleveland, OH, Dallas, TX, or Birmingham, AL.

Compensation: Base salary range $86,250.00–$172,500.00 per year. Salaries may vary by geographic location, market data, and individual skills, experience, and education. This position is incentive eligible, with payment based on company, business, and/or individual performance.

Responsibilities

• Develop anomaly detection metrics and monitoring tools to identify potential fraud signals.
• Analyze structured and unstructured data to detect suspicious activity, identify fraud patterns, and surface emerging trends.
• Collaborate with cross-functional teams to share insights and continuously improve fraud mitigation processes.
• Perform analytical tasks on large volumes of structured and unstructured data to extract actionable business insights.
• Support data gathering, data processing, and data mining for large and complex datasets.
• Build algorithms using advanced mathematical and statistical techniques, including machine learning, to predict outcomes and recommend optimal actions to management.
• Run analytical experiments in a methodical manner to identify opportunities for product and process optimization.
• Assist in presenting 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.

Requirements

• 3+ years of relevant, direct industry experience.
• Education: Master’s degree.
• Core focus areas include Analytical Thinking, Data Analytics, Data Mining, Data Science, and Machine Learning (ML).

Technologies

• Machine Learning (ML)

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)
• 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

Application and accessibility

Application window: Generally expected to be posted for two business days from 07/23/2026, though it may be longer with business discretion.

Disability accommodations: If an accommodation is required to participate in the application process, contact [email protected]. Include “accommodation request” in the subject line and provide your name, the job ID, and your preferred method of contact. Emails not related to accommodation requests will not receive responses. Applicants may also call 877-968-7762 and say “Workday” for accommodation assistance.

PNC fosters an inclusive and accessible workplace and provides reasonable accommodations to employment applicants and qualified individuals with a disability who need an accommodation to perform the essential functions of their positions.

EEO: PNC provides equal employment opportunity to qualified persons regardless of protected characteristics under law. This position is subject to requirements of Section 19 of the Federal Deposit Insurance Act (FDIA) and, for any registered role, may include SAFE Act and/or FINRA requirements related to hiring restrictions based on certain criminal history.

California residents: Refer to the California Consumer Privacy Act Privacy Notice to understand how PNC may use or disclose personal information in hiring practices.