AVP/VP – Market Risk/AI Modeling & Analytics

Madison-Davis, LLC

New York (NY)

Hybrid

USD 152,000 - 195,000

Full time

4 hours ago
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Job summary

Madison-Davis, LLC is seeking an AVP/VP for Market Risk/AI Modeling & Analytics in a hybrid New York environment. The role focuses on advancing AI capabilities for trading book risk modeling, including VaR, Stressed VaR, and stress testing, with production-grade AI solutions and automated data workflows.

Candidates should have strong Python skills, a deep understanding of market risk methodologies, and hands-on AI/data analytics experience to collaborate across Front Office, Risk, Technology,

Qualifications

  • Strong Python programming skills and solid understanding of market risk methodologies.
  • Hands-on experience with AI and data analytics to support risk modeling.

Responsibilities

  • Lead the design and implementation of Agentic AI and Generative AI solutions to automate and enhance market risk data processing, time series construction, and historical data backfilling
  • Develop scalable AI-driven frameworks for data quality monitoring, anomaly detection, and data remediation across trading book risk datasets
  • Evaluate and incorporate emerging AI technologies to improve analytical workflows and operational efficiency across the risk modeling function
  • Design and implement advanced statistical approaches to support evaluation, monitoring, and continuous improvement of AI-based models
  • Build prototypes and production-ready analytical models utilizing large-scale financial datasets; collaborate with technology teams to ensure seamless integration of analytical solutions into production environments
  • Work with model review and validation teams to ensure compliance with regulatory and firm governance standards applicable to both quantitative and AI models
  • Present analytical findings, model results, and strategic recommendations to senior management and key stakeholders across the organization

Skills

Python programming
Market risk knowledge
AI & data analytics

Job description

Title: AVP/VP – Market Risk/AI Modeling & Analytics
Office Status: Hybrid – New York, NY
Base Salary: $152k – $195k + Bonus
Overview:

This Vice President opportunity sits within the Trading Book Risk Modeling team of a global financial institution. The role offers a high-impact mandate to advance the firm's data analytics and AI capabilities in support of trading book risk modeling, combining deep quantitative analytics expertise with cutting-edge AI and Generative AI development. You'll be responsible for building production-grade solutions that enhance market risk data infrastructure, automate data processing workflows, and support key trading book risk models. These include VaR, Stressed VaR, Sensitivity Analysis, and Stress Testing. It's an ideal fit for a quantitatively rigorous professional with hands-on AI and data analytics experience; someone who pairs strong Python programming skills with a solid understanding of market risk methodologies and can collaborate effectively across Front Office, Risk, Technology, and Data teams.

Key Responsibilities:
  • Lead the design and implementation of Agentic AI and Generative AI solutions to automate and enhance market risk data processing, time series construction, and historical data backfilling
  • Develop scalable AI-driven frameworks for data quality monitoring, anomaly detection, and data remediation across trading book risk datasets
  • Evaluate and incorporate emerging AI technologies to improve analytical workflows and operational efficiency across the risk modeling function
  • Design and implement advanced statistical approaches to support evaluation, monitoring, and continuous improvement of AI-based models
  • Build prototypes and production-ready analytical models utilizing large-scale financial datasets; collaborate with technology teams to ensure seamless integration of analytical solutions into production environments
  • Work with model review and validation teams to ensure compliance with regulatory and firm governance standards applicable to both quantitative and AI models
  • Present analytical findings, model results, and strategic recommendations to senior management and key stakeholders across the organization
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