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PNC is a diversified financial services and banking company with career opportunities spanning roles across its organization. Its workplace approach emphasizes inclusion, accessibility, diversity, and community involvement, with recruiting pathways for students, graduates, and veterans. PNC also highlights its commitment to equal opportunity and compliance with employment laws, making its careers relevant to candidates seeking a large financial-services employer with a broad range of professional possibilities.
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Quantitative Analytics and Model Consultant – Data and MLOps

Quantitative analytics consultant responsible for operationalizing machine learning and AI solutions in PNC’s banking business. The role covers data pipelines, model deployment, AI agents, monitoring, validation, and regulatory documentation.

USUnited StatesOHOhioPAPennsylvaniaVAVirginia
$91,000 – $202,800 / year
On-siteFull-timeMiddleSeniorEnglish RequiredMachine Learning Engineer
AWSAzurePySparkPythonSQL

Description

  • Design, develop, and support scalable data, AI, and machine learning solutions across development and production environments
  • Transition analytical and machine learning models into production through packaging, integration, testing, and deployment
  • Create and maintain reusable CI/CD pipelines for model training, scoring, deployment, and retraining
  • Build scalable data pipelines along with reusable data and feature products
  • Develop monitoring and analytics frameworks to track model performance, stability, and data drift
  • Create AI agents and LLM-based agentic workflows using prompt engineering, RAG, tool and API integration, and orchestration
  • Build AI-agent testing and evaluation frameworks covering accuracy, consistency, hallucinations, bias, security risks, and user acceptance testing
  • Deploy production AI agents with guardrails, human oversight, and comprehensive logging
  • Track AI-agent quality, adoption, and operating costs over time
  • Assess business impact by defining success measures, establishing baselines, and monitoring results such as lift, loss reduction, and efficiency gains
  • Collaborate with data scientists, model owners, technology teams, business stakeholders, and lines of business
  • Conduct advanced quantitative analysis and model development to inform business decisions
  • Create model frameworks, enhance and monitor existing models, and perform model validation
  • Maintain ongoing communication with model owners and developers throughout review activities
  • Assess model theory, design, implementation, data quality, and integrity using qualitative and quantitative methods
  • Evaluate model risk and document conclusions about model strengths and limitations
  • Prepare and review documentation supporting model validation and regulatory compliance

Requirements

  • Bachelor’s degree in data science, engineering, mathematics, statistics, or a related quantitative discipline
  • Professional experience supporting machine learning, analytics, DevOps, or MLOps environments
  • Experience deploying and supporting analytical or machine learning solutions in enterprise settings
  • Programming experience with Python, SQL, R, or PySpark
  • Hands-on experience with AWS or Azure
  • Working knowledge of machine learning workflows and model deployment practices
  • Strong analytical and problem-solving capabilities
  • Effective communication and presentation skills
  • Ability to influence and collaborate with technical and business stakeholders
  • Experience contributing in highly collaborative, cross-functional environments
  • Strong stakeholder engagement and relationship management skills
  • Banking, financial services, lending, or risk management experience is preferred
  • Familiarity with model governance, monitoring, and production support processes is preferred
  • Understanding of data engineering and enterprise data ecosystems is preferred
  • Typically, at least five years of relevant industry experience is required at this level
  • Candidates without a degree may be considered with a comparable combination of education, job-specific certifications, and experience
  • No certifications are required
  • No licenses are required
  • PNC does not provide employment visa sponsorship or participate in STEM OPT

Benefits

  • Medical and prescription drug coverage, including a Health Savings Account option
  • Dental and vision plan options
  • Life insurance for employees and eligible spouses or children
  • Short-term and long-term disability coverage
  • 401(k) plan with a PNC matching contribution
  • Pension plan
  • Employee stock purchase plan
  • Dependent care reimbursement account
  • Backup child and elder care services
  • Adoption, surrogacy, and doula reimbursement
  • Educational assistance, including select programs that are fully funded
  • Wellness program with financial incentives
  • Maternity and parental leave
  • Up to 11 paid holidays annually
  • Nine occasional absence days annually
  • 15 to 25 vacation days per year, based on career level
  • Incentive-eligible compensation tied to company, business, and/or individual performance

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