Derivative Counterparty Risk Manager

U.S. Bank is seeking a Quantitative Analyst to provide oversight on derivative business growth covering rates and foreign exchange derivatives ensuring such products are appropriately configured in counterparty model and risk measures are accurately quantified. The person will also have oversight on all other derivatives products that are used for hedging activities. The hedging product sets include but not limited to credit derivative, credit risk transfer products, equity like derivatives such ETF options. Additional responsibilities include activities that are required regulatory compliance such as risk process for accepting non-standard securities collateral (e.g. corporate bonds). Counterparty risk management for secured financing transactions and its appropriate configuration in risk metrics model will also be part of the responsibilities.

The counterparty risk management function is responsible for the management and control of counterparty risk at US Bank.  The group provides independent review of counterparty risk across the business, producing detailed analysis of the derivative portfolio for internal and external constituents and manage the control framework under which counterparty risk is governed.

Serves as an escalation point in interactions with stakeholders across Front Office and Quantitative Model teams including development of teams and technology on various market data-related topics: Daily market data quantitative analysis, Data quality remediation efforts (e.g., designing quantitative key performance indicators so as to measure quality of data, or, quantitative approaches to fill missing data, working with Front Office desks), Communicates market data quality issues to downstream users

Manages requests for new market data (e.g., participating in new product approval process, interacting with vendor procurement teams). Ensures team adheres to firm-wide policies for data governance and controls. Coordinates with all external model vendors and internal quantitative partners around all key risk analytic topics. Works with model development and validation groups in ensuring the accuracy and reasonableness of the stress test and other model assumptions. Partners with them in ensuring on smooth maintenance of ongoing monitoring of models. Review all counterparty related model documentation and sign-off on key assumptions. Liaison with technology and other key groups regarding counterparty risk infrastructure and processes.

Preferred Skills/Experience

• Experience in capital markets, industry experience within the specific sector of the position, or a combination of both

• Master’s degree or higher in a quantitative field such as mathematics, engineering, physics, or statistics

• Required strong Python & SQL

• Experience financial modeling and strong understanding of stochastic processes  

• Experience building an efficient large scale and complex market data operations/end to end market data engineering processes in a sales and trading environment

• Experience working with quant teams developing market data management systems which allow for efficient data retrieving to optimize modeling approaches

• Experience leading large teams/multiple business partners, overseeing business as usual market data operations with strong governance processes and controls

• Knowledge and understanding of traded derivative and cash products across all asset classes to effectively have discussions with Front Office traders, Market Risk Officers, and Risk Analytics team

• Experience overseeing the development and implementation of quantitative methods for data quality checks and remediation techniques including statistical data filling methods and proxying

• Understanding of how market data impacts the downstream uses

• Counterparty credit risk and CVA

• Understanding of major market data sources (e.g., Bloomberg, Reuters, Markit)

• Market data object construction methods for curves and volatility surfaces

• Risk factor types across asset classes

• Market data related to regulatory requirements 

• Experience in quantitative or complex data management field

• Experience working with large scale and complex data management systems

• Proficient in Python and SQL (reading and writing queries)

NOTE:  This role offers a hybrid/flexible schedule, which means there's an in-office expectation of 3 or more days per week and the flexibility to work outside the office location for the other days.