The Tidal Financial Group is a leading ETF investment technology platform dedicated to creating, operating, and growing ETFs. We combine expertise and innovative partnership approaches to offer comprehensive, value-generating ETF solutions. 

Our platform offers best-in-class strategic guidance, product planning, trust and fund services, legal support, operations support, marketing and research, and sales and distribution services.

About the role:

Tidal’s Assistant Vice President (“AVP”) of Financial & Emerging Risk Management, Stress Testing and AI & Automation is a dynamic multi-disciplinary role that will be a valued contributor in delivering and managing our AI-driven Program target state. The AVP will leverage their technical capabilities to use automation, AI and modeling to support our target state mission, which will deliver a fully integrated Program that maximizes the efficiency and value of its processes and reporting. The core components of our Program the AVP will support include the following: Financial Risk Management (Market, Credit/Counterparty, Liquidity), Emerging Risk Management, Stress Testing and AI & Automation including Risk Intelligence.

Reporting directly to the VP of Risk Management, the candidate fortunate to earn our exceptional AVP career opportunity will bring a passionate, entrepreneurial & disciplined mindset towards ensuring we maximize our Program’s contribution and value to Tidal’s continued growth and operational complexity.

What you'll do:

• Financial Risk Management: Build and manage a Financial Risk Management program that includes counterparty & credit, market, and liquidity risk identification, assessment, controls and risk appetite limits at the enterprise and across all funds.
• Derivatives Risk Management Program (DRMP) – Tidal’s DRMP satisfies SEC Rule 18f-4 and is one of the largest DRMPs in the country. Earn an opportunity to become a designated 18f-4 Derivative Risk Manager (DRM) by optimizing our Value-at-Risk (“VaR”), Stress Testing and Backtesting data and reporting using automation, AI and quantitative modeling.
• Liquidity Risk Management Program (LRMP) – Manage Tidal’s LRMP that satisfies SEC Rule 22e-4 including ensuring defensible liquidity classification of fund investments including satisfaction of illiquid investment limits and optimizing processes and reporting using automation, AI and quantitative modeling.
• Emerging Risk Management: Build and manage an Emerging Risk Management program that identifies, assesses and monitors emerging risks facing Tidal to drive prudent discussions and decisions on paths to potentially mitigate their impact.
• Stress Testing: Build and manage a Stress Testing Program with stress scenarios designed based on material risks, control weaknesses & issues/incidents to stress risks & related risk appetite. Utilize stress scenarios to understand impact on capital, liquidity, operations & ETFs ability to satisfy regulatory limits.
• Risk Intelligence - Design and implement Tidal’s Risk Intelligence data and reporting using automation, AI (ex. LLM, machine/deep learning), quantitative modeling, and visualization tools to deliver highly efficient data-driven risk insights and forward-looking predictive analytics & forecasts to drive proactive risk-informed decisions.
• Integrated Central System – Design and implement our Program’s integrated central system that will store, review, update and link our risks, controls, risk appetite limits, issues, counterparties, third-party vendors & policies/governing documents.
• Cross-Functional Leadership - A trusted partner across Tidal’s growth-oriented, entrepreneurial culture by providing balanced challenge, thoughtful insights, and practical recommendations.

Qualifications:

• Bachelor’s degree in Data Science, Econometrics, Advanced Mathematics, Financial Engineering, Computer Science or related technical degrees.
• 5+ years of relevant experience in risk management and/or related quantitative discipline within asset/investment management, ETF platforms, or broader financial services preferred.
• Demonstrated knowledge and experience using AI (LLM, machine/deep learning) and building quantitative models to deliver forward-looking predictive analytics and forecasts.
• Demonstrated knowledge and experience in building and using automation and data visualization tools to streamline complex processes and build reporting including dashboards with insightful and actionable information.
• Practical understanding of enterprise risk & governance frameworks including risk identification & assessment, controls, risk appetite limits and stress testing preferred.
• Practical understanding of trading, ETFs, derivatives risk, including options, swaps, futures, structured instruments, margining, collateral, and liquidity risk preferred.
• Exceptional written and verbal communication skills, with ability to translate complex issues into clear and actionable decisions.
• Ability to thrive in a fast-paced, high-growth, entrepreneurial environment, balancing structure with adaptability.
• Strong interpersonal skills and ability to influence stakeholders.