Senior Python Developer

Summary:

• Quantitative Services (QS) team is involved in an enterprise wide IBOR transition initiative that will replace existing IBOR index and funding curves with the risk free SOFR/ESTER.
• The key objective of this initiative is to replace discounting and index curves that currently used to valuate financial derivatives and loans due to IBOR decommission. QS is the business owner for several key processes like UMR and Risk Optimization.
• As part of this initiative QS will be responsible for providing regression and impact test, assessing exposure impacted, assisting hedging execution and driving the overall migration from legacy yield curves to new risk free curves.

Responsibilities:

• Apply mathematical or statistical techniques to address practical issues in overall IBOR transition program, such as derivative valuation, trade hedging, risk management, CSA transition and other regulatory requirements.
• Knowledge of yield curve construction and Rates derivative valuation. Build approach to assess Initial Margin (IM) and Present Value (PV) impact across all asset classes with different funding curves.
• Run regression testing and impact analysis on LIBOR/EURIBOR decommission. Assess the execution of CCP hedging position and produce management reporting.
• Understand quantitative libs and their usage to assist migration of existing FO/Risk pricing tools from IR toolkit to GDA functors.
• Assess IM impact under Uncleared Margin Rules (UMR). Verify the model inputs (e.g. market data) and the calculations.
• Ensure the firm's IM calculations are accurate after switching to risk free yield curves. Identify and establish control processes that will mitigate future IA calculation errors.
• Work directly with front office, business support and technology teams to enhance risk optimization approach to be consistent with IBOR decommission. Provide analysis to various stakeholders.

Requirements:

• Master degree or higher in Computer Science, Mathematics, Financial Engineering, Economics or related quantitative field.
• 2+ years of experience working in a quantitative risk, middle office, or front office role Python programming, SQL, VBA experience.
• Knowledge of broad range of OTC derivative, FIF, Repo and loan products, Credit Risk, VaR and XVA Models for FO or Risk valuation.
• Ability to leverage quantitative and programming skills to build deep knowledge of the financial analytical libraries and infrastructure.
• Experience with handling large data set with the ability to transform information into concise presentations with sound business conclusions and recommendations.

Skills:

• Analytical and problem solving skills with the ability to interpret large amounts of information and conceptualize the impact across operational processes. ? Excellent communication & analytical skills.
• CFA and / or CQF is a plus. Knowledge of the current financial regulatory environment.
• Python
• quantitative risk
• SQL
• VBA
• CFA