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PNC

Quantitative Analytics & Model Consultant - Data Operations and Machine Learning Operations

Cleveland, OH, United States

Base Salary: $91,000.00 – $202,800.00

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Job details

Pay: Base Salary: $91,000.00 – $202,800.00
Posting language: English
Posted: Oct 7, 2026

Original job description

VA - Vienna (22182)

VA - Tysons Corner

NJ - East Brunswick

DC - Washington (20006)

PA - Pittsburgh (15222)

OH - Cleveland (44114)

Full time

R235713

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 Quantitative Analytics & Model Consultant within PNC's Data Operations and Machine Learning Operations organization, you will be based in Pittsburgh, PA; Cleveland, OH; East Brunswick, NJ; Washington, DC; or Tyson's Corner, VA.

Position Overview:

PNC is seeking a Quantitative Analytics & Model Development Consultant to join our Machine Learning Operationalization (MLOps) team. This role is responsible for designing, developing, and supporting scalable Data, AI and machine learning solutions that enable advanced analytics across the enterprise.

The successful candidate will combine expertise in data engineering, cloud infrastructure, DevOps, and MLOps to help support and design analytical and machine learning solutions in development and production environments. This individual will partner closely with data scientists, technology teams, business stakeholders, and lines of business to ensure solutions are reliable, scalable, secure, and operationally efficient.

Key Responsibilities:

Model Deployment: Partner with data scientists to move machine learning and analytical models from development into production, including packaging, integration, testing, and deployment.
ML Pipelines and Automation: Build and maintain automated, reusable pipelines (CI/CD) for model training, scoring, deployment, and retraining, using cloud and infrastructure-as-code tools where applicable.
Data and Feature Engineering: Develop scalable data pipelines and reusable data and feature products that provide reliable, high-quality inputs to models.
Model Monitoring and Analytics: Develop model monitoring and analytic frameworks that can be scaled to support many models, tracking performance, stability, data drift.
AI Agent Development: Design and build AI agents and agentic workflows using large language models (LLMs), including prompt design, retrieval-augmented generation (RAG), tool and API integration, and orchestration.
AI Agent Testing and Evaluation: Develop testing and evaluation frameworks for AI agents covering accuracy, consistency, hallucinations, bias, and security risks (e.g., prompt injection), and support user acceptance testing (UAT).
AI Agent Implementation: Deploy AI agents into production with appropriate guardrails, human-in-the-loop controls, and logging, and monitor their quality, usage, and cost over time.
Business Impact Measurement: Measure the business value of deployed models and AI solutions by defining success metrics, setting baselines, and tracking actual results (e.g., lift, loss reduction, efficiency gains) against expected outcomes.
Stakeholder Partnership: Work with data scientists, model owners, technology teams, and lines of business to understand requirements and deliver reliable, scalable solutions.

Required Qualifications:

Bachelor’s degree in data science, Engineering, Mathematics, Statistics, or a related quantitative field.
Build scalable frameworks and reusable components for developing, integrating, testing, and deploying ML models and AI agents across the data science lifecycle
Experience supporting machine learning, analytics, DevOps, or MLOps environments.
Experience deploying and supporting analytical or machine learning solutions in enterprise environments.
Programming/Coding experience in Python, SQL, R, or PySpark.
Experience with Cloud Platforms: AWS or Azure
Understanding of machine learning workflows and model deployment concepts
Strong analytical and problem-solving skills.
Strong communication and presentation skills
Ability to influence and collaborate across technical and business teams.
Experience working in highly collaborative, cross-functional environments
Strong stakeholder engagement and relationship management capabilities.

Preferred Qualifications:

Banking, financial services, lending, or risk management experience.
Familiarity with model governance, model monitoring, and production support processes.
Understanding of data engineering and enterprise data ecosystems

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 complex quantitative analyses and models development to support decision-making by running quantitative strategies.
Develops new model frameworks by supporting the line of business. Refines, monitors, and validates existing models. Conducts on-going communication with model owners and model developers during the course of the review. Works with large data to create models.
Performs advanced qualitative and quantitative assessments on all aspects of models including theoretical aspects, model design and implementation as well as data quality and integrity. Reviews reports and associated quantitative analysis. Validates existing models and assesses model risks.
Evaluates identified model risks and reaches conclusions on strengths and limitations of the model.
Prepares and analyzes detailed documents for validation and regulatory compliance, using applicable templates.

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, Credit Risks, Data Analytics, Financial Analysis, Model Development, Operational Risks, Quantitative Models, Risk Appetite

Competencies

Bank Quantitative Analysis, Consulting, Data Gathering and Reporting, Effective Communications, Predictive Analytics, Quantitative Techniques, Regulatory Environment - Financial Services, Testing

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 a degree, a comparable combination of education, job specific certification(s), and experience (including military service) may be considered.

Education

Bachelors

Certifications

No Required Certification(s)

Licenses

No Required License(s)

Language Assessments

No Required or Preferred Language Assessments

Pay Transparency

Base Salary: $91,000.00 – $202,800.00

Salaries 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 10/06/2026, 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 AccommodationRequest@pnc.com . 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 877-968-7762 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

Refer to the California Consumer Privacy Act Privacy Notice (https://content.pncmc.com/live/pnc/aboutus/HR/Onboarding/PNC_CCPA_Privacy_Disclosure_Employee.pdf) to gain understanding of how PNC may use or disclose your personal information in our hiring practices.

For nearly 160 years, PNC has strived to make a meaningful impact for our employees, customers, communities, and shareholders. We believe our success and positive reputation are built on open and honest dialogue, an unwavering focus on smart risk management, relationship-based customer service and community investments. Our inclusive workplace allows our employees to be heard, valued, and developed to do their best work.

Being a great place to work means we are making a lasting difference for everyone we serve. Check out the top reasons to join PNC.

PNC’s total rewards package includes things like time off, benefits, learning and career development, wellness programs, recognition and much more. The benefits and programs highlighted below are just a sampling of what PNC offers its employees. To learn more, visit our Total Rewards page (https://careers.pnc.com/global/en/total-rewards) .

If you're not ready to apply yet, or you'd like to learn more about PNC, join the Talent Community to receive regular updates on what's happening at PNC and available career opportunities. Click to join! (https://flows.beamery.com/pnc/tc-signup)

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More about this job

Skills

Machine learning
Google Analytics
Data engineering
DevOps
Packaging
Security threats
Statistics
ML
Python
SQL
R
PySpark
AWS
Microsoft Azure
Problem solving
Communication skills
Presentation skills
Stakeholder management
Risk management
Decision making
Create model
Regulatory compliance
Analytical skills
Data analysis
Financial analysis
Reporting

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