I am a Principal Consultant in the Quant Services division of LSEG, where I partner with tier-one investment banks, hedge funds, and risk technology teams to design, validate, and implement quantitative models for counterparty credit risk and derivative pricing. My work spans CVA, DVA, FVA, and PFE model validation, regulatory compliance with frameworks such as SS1/23 and FRTB, and the deployment of open-source risk infrastructure using the Open Source Risk Engine (ORE).
I hold a PhD in Applied Mathematics from the University of Limerick, where my research focused on describing the dynamics of complex systems (such as online social networks and popularity dynamics) using mathematical modelling and large-scale data analysis. This background in applied statistics and network science now informs my approach to building robust, mathematically rigorous financial risk analytics.
My technical toolkit includes Python (NumPy, SciPy, pandas, QuantLib Python), C++ for performance-critical pricing components, and R for statistical analysis and diagnostics. I also regularly contribute to LSEG’s Ahead of the Curve podcast series, discussing ORE developments, model risk regulation, and the future of quantitative risk management.
Interests
- Counterparty Credit Risk (CCR)
- XVA (CVA / DVA / FVA)
- Derivative Pricing & Valuation
- Model Risk Management
- Quantitative Finance
Education
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PhD in Applied Mathematics, 2017-2021
University of Limerick
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BSc. in Financial Mathematics, 2013-2017
University of Limerick
