Data Science Expert - Emerging Fraud Risk Lead

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 Science Expert - Emerging Fraud Risk Lead within PNC's Enterprise Fraud organization, you can be based in Birmingham, AL; Phoenix, AZ; Lakewood, CO; Strongsville, OH; Cleveland, OH; Pittsburgh, PA; or Dallas, TX.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

The Data Science Expert - Emerging Fraud Risk Lead is a highly visible individual contributor responsible for identifying and mitigating emerging fraud risks before they become significant business impacts.

This role will initially focus on Credit Card and Lending fraud and will serve as a critical bridge between Fraud Monitoring, Incident Response, Countermeasures Analytics, and Fraud Strategy teams.

Core Responsibilities

• Establish and mature the Emerging Fraud Risk capability, creating a scalable and repeatable pipeline of fraud detection and mitigation opportunities.
• Proactively identify emerging fraud threats, attack patterns, and vulnerabilities across Credit Card and Lending products before they result in significant losses.
• Apply advanced analytics, machine learning, anomaly detection, behavioral modeling, network analysis, and other data science techniques to uncover evolving fraud risks and validate risk hypotheses.
• Conduct complex investigations into emerging fraud behaviors, translating analytical findings into actionable recommendations and control opportunities.
• Serve as the bridge between portfolio monitoring and incident response teams, ensuring early risk indicators are prioritized and addressed proactively.
• Partner with Fraud Strategy, Countermeasures Analytics, Monitoring, Risk Management, Product, and Technology teams to develop and advance fraud mitigation solutions.
• Assess, design, and recommend detection strategies, fraud signals, and control enhancements for operational implementation.
• Lead end-to-end analytical initiatives utilizing large-scale structured and unstructured data to generate business insights and improve fraud prevention capabilities.
• Provide subject matter expertise in fraud analytics, machine learning, and risk modeling while establishing best practices for experimentation, model validation, and detection development.
• Influence strategic priorities and investment decisions through data-driven insights, risk assessments, and executive-level presentations.
• Evaluate emerging analytical methodologies and technologies to enhance fraud detection effectiveness and strengthen the enterprise fraud risk framework.
• Contribute thought leadership and drive innovation in fraud analytics and emerging risk management across the organization.

Preferred Skills & Experience

• Experience in fraud analytics, data science, machine learning, or risk management, preferably within Credit Card, Lending, or Financial Services.
• Experience using Spark / PySpark to process large-scale datasets and develop scalable analytical and machine learning solutions in a production environment.
• Advanced experience using SQL , Python , and data science libraries to extract, analyze, and model large datasets in support of fraud detection and risk management initiatives.
• Hands-on experience developing, testing, and validating machine learning models using tools such as Scikit-learn , XGBoost , LightGBM , Pandas , and NumPy , or comparable technologies.
• Strong foundation in statistics, experimentation, and model validation.
• Proven ability to develop and deploy machine learning models and analytical solutions that identify emerging risks and drive measurable business outcomes.
• Experience applying advanced analytical techniques, including anomaly detection, predictive modeling, clustering, behavioral analytics, and network/graph analysis to uncover fraud patterns and validate risk hypotheses.
• Strong analytical and problem-solving skills, with experience investigating complex fraud trends and translating findings into actionable recommendations.
• Demonstrated leadership through influence, including leading analytical initiatives and driving results across cross-functional teams without direct management responsibility.
• Strong communication and stakeholder management skills, with the ability to influence technical and business audiences and present recommendations to senior leaders.
• Experience partnering across fraud, risk, strategy, business, and technology teams to operationalize data-driven solutions and fraud controls.

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, Machine Learning (ML), PySpark, Python (Programming Language), Statistics

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. Higher level education such as a Masters degree, or PhD is desirable. Industry experience is typically 8 + years. Specific certifications are often required. In lieu of a degree, a comparable combination of education, job specific certification(s), and experience (including military service) may be considered.

Education

Masters

Certifications

No Required Certification(s)

Licenses

No Required License(s)

Language Assessments

No Required or Preferred Language Assessments

Pay Transparency

Base Salary: $133,000.00 – $217,700.00Salaries may vary based on geographic location, market data and on individual skills, experience, and education. This role is incentive eligible with the payment based upon company, business and/or individual performance.

Application Window

Generally, this opening is expected to be posted for two business days from 08/21/2026, although it may be longer with business discretion.

Benefits

PNC offers a comprehensive range of benefits to help meet your needs now and in the future. Depending on your eligibility, options for full-time employees include: 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.In addition, PNC generally provides the following paid time off, depending on your eligibility: 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.

To learn more about these and other programs, including benefits for full time and part-time employees, visit pncthrive.com .

Disability Accommodations Statement

If an accommodation is required to participate in the application process, please contact us via email at View email address on us.fitly.work. Please include “accommodation request” in the subject line title and be sure to include your name, the job ID, and your preferred method of contact in the body of the email. Emails not related to accommodation requests will not receive responses. Applicants may also call View phone number on us.fitly.work and say "Workday" for accommodation assistance. All information provided will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

At PNC we foster an inclusive and accessible workplace. We provide reasonable accommodations to employment applicants and qualified individuals with a disability who need an accommodation to perform the essential functions of their positions.

Equal Employment Opportunity (EEO)

PNC provides equal employment opportunity to qualified persons regardless of race, color, sex, religion, national origin, age, sexual orientation, gender identity, disability, veteran status, or other categories protected by law.

This position is subject to the requirements of Section 19 of the Federal Deposit Insurance Act (FDIA) and, for any registered role, the Secure and Fair Enforcement for Mortgage Licensing Act of 2008 (SAFE Act) and/or the Financial Industry Regulatory Authority (FINRA), which prohibit the hiring of individuals with certain criminal history.

California Residents

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