Production ML & Quant Analytics Consultant

PNC; Cleveland (OH); On-site; USD 91,000 - 203,000; Full time

Job summary

PNC is seeking a Quantitative Analytics & Model Development Consultant to join the Machine Learning Operations team. This role designs, develops, and supports scalable Data, AI and ML solutions across the enterprise, based in Pittsburgh, Cleveland, or Tyson's Corner.

You will partner with data scientists, tech teams, and business stakeholders to ensure solutions are reliable, secure, and cost-efficient. The position requires a blend of data engineering, cloud, DevOps, and MLOps expertise.

Qualifications

• Bachelor’s degree in data science/Engineering/Mathematics/Statistics.
• 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

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.

Skills

Python

SQL

R

PySpark

Education

Bachelor's degree in data science, Engineering, Mathematics, Statistics

Tools

AWS

Azure

Job description

PNC is seeking a Quantitative Analytics & Model Development Consultant to join the Machine Learning Operations team. This role designs, develops, and supports scalable Data, AI and ML solutions across the enterprise, based in Pittsburgh, Cleveland, or Tyson's Corner.

You will partner with data scientists, tech teams, and business stakeholders to ensure solutions are reliable, secure, and cost-efficient. The position requires a blend of data engineering, cloud, DevOps, and MLOps expertise.