Risk Management - Quant Modeling Lead - Vice President

JPMorgan Chase & Co. • Jersey City, NJ

3d • $147,250 - $215,000

About The Position

As a Risk Management Quant Modeling Lead / Vice President within the Model Risk Governance and Review Consumer & Community Banking Operations & Digital Channels team, you independently assess and challenge models and AI systems supporting digital customer experiences and operational decision-making across chatbots, voice AI assistants, mobile applications, and web platforms. You collaborate with model developers, product and channel stakeholders, governance partners, and senior leadership to ensure solutions are conceptually sound, fit for purpose, well-controlled, and compliant with the Firm’s Model Risk Management framework. You stay current with emerging generative AI, large language model, and agentic capabilities, translating technical findings into clear, actionable recommendations that enhance customer outcomes and strengthen the Firm’s risk posture.

Requirements

• Master’s or PhD in Mathematics, Statistics, Computer Science, Engineering, Economics, Quantitative Finance, or a related field.
• Minimum 6+ years of relevant hands-on experience in model risk, model validation, quantitative risk, or applied ML oversight.
• Hands-on experience with applied AI/ML and strong understanding of GLMs, tree-based models, deep learning, transformers, LLMs, and modern AI techniques.
• Strong foundation in statistics and machine learning, including estimation, testing, bias/variance, overfitting, performance measurement, and uncertainty.
• Experience with Python and ML frameworks such as PyTorch, TensorFlow, XGBoost, or LightGBM.
• Excellent written and verbal communication skills, with the ability to explain complex technical topics clearly and precisely.
• Strong risk and control mindset, with demonstrated ability to identify, assess, and escalate model and AI risks.

Nice To Haves

• Knowledge and experience with LLM technologies and modern AI patterns, including prompt engineering, RAG architectures, agentic AI systems, context engineering, agent tool use and skills, and evaluation frameworks.
• Experience with conversational AI or digital assistant solutions (chat and/or voice), including practical exposure to testing, review, or ongoing performance monitoring.
• Experience designing or reviewing evaluation approaches for agentic systems, such as task success and containment, human-in-the-loop review, offline test suites, and safety and quality checks.
• Experience validating risk, customer experience, and/or decision support models used in digital channels or operations.
• Experience in financial services and collaborating with business, product, technology, compliance, and regulatory stakeholders.

Responsibilities

• Lead and conduct independent model validation and governance activities across CCB Operations & Digital Channels.
• Assess conceptual soundness, implementation accuracy, performance, limitations, and business suitability of statistical, machine learning, and AI systems used in digital journeys and operational workflows.
• Review traditional regression and decision tree models, advanced machine learning models, neural networks, transformers, recommender systems, reinforcement learning, Generative AI, LLM-based solutions, and agentic systems.
• Design, review, or evaluate agentic systems, including voice bots and conversational agents, considering end-to-end lifecycle elements such as intent routing, tool use, guardrails, and evaluation and monitoring approaches.
• Evaluate model and agent performance using appropriate methodologies, including back-testing, benchmark tests, stability and drift analysis, outcome analysis, and controlled experiments where applicable.
• Assess model risk and control posture for LLM and agentic solutions, including reliability, explainability, bias and fairness, data usage, privacy and security, prompt-injection resilience, and safe failure modes consistent with MRGR expectations.
• Communicate model risk assessments and validation findings through technical reports and presentations tailored to technical and non-technical audiences.
• Maintain the model risk control apparatus and serve as a primary point of contact for product, channel, technology, and governance stakeholders.
• Stay current with emerging AI and LLM developments and assess their appropriate, controlled application within business workflows.
• Escalate material model issues appropriately and track remediation actions to closure.
• Collaborate with model developers, business stakeholders, governance teams, and senior leadership to drive timely, pragmatic risk outcomes.

Benefits

• Competitive total rewards package, including base salary determined by role, experience, skill set, and location.
• Eligible roles may receive commission-based pay and/or discretionary incentive compensation in cash and/or forfeitable equity.
• Comprehensive health care coverage.
• On-site health and wellness centers.
• Retirement savings plan.
• Backup childcare.
• Tuition reimbursement.
• Mental health support.
• Financial coaching.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior