Data Scientist Senior - Internal Audit

PNC•Downers Grove, IL

1d•$91,000 - $185,900•Onsite

About The Position

PNC is hiring a Senior Data Scientist within its Internal Audit organization. The role is based in Cleveland, Ohio; Pittsburgh, Pennsylvania; Raleigh, North Carolina; or Birmingham, Alabama. Internal Audit provides independent, objective assurance and consulting services, using data, emerging technologies, and analytical methods to improve organizational performance and identify risk. The Senior Data Scientist develops advanced analytical, machine learning, and AI-enabled solutions to improve audit effectiveness, operational insights, risk identification, and strategic decision-making. The role partners with audit professionals, business stakeholders, and technology teams to turn business challenges and audit objectives into scalable, production-ready analytics and data products. It also contributes to the development of Internal Audit’s data science, automation, and AI capabilities. The position leads analytical projects using structured and unstructured data, directs data gathering and processing, and develops algorithms and models to predict outcomes and recommend actions. It leads methodical analytical experiments, presents insights through visualization and data storytelling, and collaborates with data architects, analysts, engineers, and visualization specialists. The role requires a master’s degree and typically five or more years of relevant industry experience; a comparable combination of education, certifications, and experience may be considered in lieu of a degree. The position is incentive eligible, and the listed base salary range is $91,000 to $185,900.

Requirements

Master’s degree; a comparable combination of education, job-specific certifications, and experience, including military service, may be considered in lieu of a degree.
Typically five or more years of industry-relevant experience.
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 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, text analytics, document intelligence, topic modeling, and unstructured data analysis.
Experience developing, validating, deploying, and monitoring production analytics or machine learning solutions.
Familiarity with package, dependency, and artifact management tools such as Artifactory, Conda, or pip, or similar technologies.
Familiarity with data visualization platforms such as Power BI, Tableau, or similar tools.
Strong problem-solving and critical-thinking capabilities.
Ability to influence stakeholders and communicate effectively with technical and business audiences.
Ability to manage multiple priorities and deliver high-quality solutions in a dynamic environment.
Strong collaboration skills and interest in mentoring and developing others.
Must meet applicable requirements related to Section 19 of the Federal Deposit Insurance Act and, for registered roles, applicable SAFE Act and/or FINRA requirements.
Employment visa sponsorship and STEM OPT participation are not provided for this position.

Nice To Haves

Experience with generative AI, large language models, prompt engineering, retrieval-augmented generation, AI agents, or related technologies.
Understanding of AI governance, model risk management, and responsible AI practices.
Preferred skills include analytical thinking, competitive advantages, data analytics, data mining, data science, and machine learning.

Responsibilities

Lead the design, development, testing, deployment, and maintenance of advanced analytics, machine learning, and AI-enabled solutions for Internal Audit.
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 to improve audit planning, testing, continuous monitoring, and reporting.
Build scalable, maintainable, reusable analytical frameworks, workflows, and data products across the audit lifecycle.
Identify opportunities to use automation, machine learning, and generative AI to improve audit processes and risk identification.
Collaborate with technology, data, and enterprise partners on model deployment, productionization, data pipelines, and ongoing solution maintenance.
Ensure analytical solutions meet governance, validation, testing, documentation, and lifecycle-management standards.
Communicate analytical results and strategic recommendations to technical and non-technical audiences, translating findings into actionable business insights.
Mentor and provide technical guidance to team members, promoting best practices in data science, machine learning, software development, and analytics engineering.
Contribute to Internal Audit’s data science, automation, and AI capabilities through innovation, thought leadership, and continuous improvement.
Lead implementation of analytical projects that use structured and unstructured data to produce actionable business insights.
Direct data gathering, processing, and mining of large and complex datasets.
Lead development of algorithms using advanced mathematical and statistical techniques to predict business outcomes and recommend actions to management.
Lead analytical experiments to identify opportunities for product and process optimization, and present business insights using visualization technologies and data storytelling.
Partner with data architects, data analysts, data engineers, and visualization experts to develop data-driven business solutions.
Focus on customer needs and satisfaction in business decisions, and effectively manage risks in accordance with PNC’s Enterprise Risk Management Framework.

Benefits

Medical and prescription drug coverage, including a Health Savings Account feature, for eligible full-time employees.
Dental and vision options.
Employee and spouse/child life insurance.
Short- and long-term disability protection.
401(k) plan with PNC match.
Pension and stock purchase plans.
Dependent care reimbursement account.
Back-up child and elder care.
Adoption, surrogacy, and doula reimbursement.
Educational assistance, including select fully paid programs.
Wellness program with financial incentives.
Maternity and/or parental leave, subject to eligibility.
Up to 11 paid holidays each year, subject to eligibility.
Nine occasional absence days each year, unless otherwise required by law.
Between 15 and 25 vacation days each year, depending on career level and eligibility.
Incentive compensation based on company, business, and/or individual performance.