App developer and investment banker to take your business to the next level
Marden, United Kingdom
software engineering, financial markets and client relationship management.
I have top MSc Computer Science grades with a final year average of over 80% (Distinction) and the
academic award for Best Dissertation for an Android application I developed. I have excellent
computer security skills, with 100% in the final exam for the Information Security module leading to
an overall grade of 97%. I have very strong SQL and database skills, with both academic practical
experience in bank and start-up environments.
I have won an academic award for an Android app I developed which makes use of the Google Maps
API, Firebase, Stripe, MangoPay and has its own RESTful API to enable client-server communication.
The app was developed in Kotlin and PHP and allows users to find and share parking spaces. It also
allows car park owners to accept mobile payments for their service.
My finance roles have involved developing financial models from the bottom-up, modelling real
world behaviour and its impact on pricing (e.g. mortgage pre-payment) and end-to-end transaction
management from origination through to structuring and execution. I reached my first Vice-
President role after 3 years in recognition of my work and ambition.
Ongoing relation / part-time
Full time contractor
Front Office Tool Development
• Built front office tools for monitoring and modelling prepayments on a variety of mortgage
and loan pools to price Balance Guarantee Swaps, including delinquency data, using Python and VBA.
o The tool collated millions of lines of mortgage-level structured data based on known
statistical relationships (e.g. product sensitivity to market interest rates) and enhanced this with data from bank systems based on other known relationships
(e.g. geographic prepayment probabilities).
o This was done through a combination of SQL where possible and a self-built Python
tool to source and compress data not accessible via SQL (e.g. from CSV files, log files and Excel spreadsheets).
o Involved collation of data from front-to-back bank systems and deep understanding of structure of data throughout the bank, as well as understanding of InfoSec,
Compliance and Operational risks inherent in this data access.
o Finally, live market data from Bloomberg BQL and the bank's market making desk
were gathered via an internal API.
o These collated mortgage data were then evaluated at an individual level for a multi-
million mortgage pool to determine the historical prepayment for each loan, the
sensitivity of that prepayment to prevailing interest rates at that time, sensitivity to other identified factors (e.g. geography, product) and to forecast future
o These future prepayments were aggregated for the loan pool and tested against
observed outcomes on historical data and then live data.
o Once the accuracy of the process was confirmed, this approach was used as part of a wider valuation to price and trade a series of hedging derivatives for the loan pool.
o Project was fully documented and was easily extensible; it will likely be used on
future loan securitisation vehicles as the principles can be applied broadly.
• Used combination of live data from Bloomberg BQL and live in-house market making pricing
to generate derivative execution performance data to allow us to track performance
• Prototyped a derivative pricing tool using Machine Learning techniques to forecast Constant
Prepayment Rates (CPRs)
• Built an execution analysis tool in VBA to monitor performance against our benchmarks
Debt Capital Markets Investment Banking
• Built relationships with new clients and managed the relationship from origination through
to execution of deals
• Created financial models from scratch based on pre-emptive understanding of client
requirements and proposed these solutions to clients
• Structured and executed deals involving:
o Interest rate derivatives
o Inflation derivatives
o Private Placements
o Public bonds
• This role involved taking ownership of the entire client origination and trading process and generating revenue for the bank from a blank slate
• Strong mathematical knowledge of derivative modelling
• Trading of options (caps, floors and structured combinations of these), balance guarantee
swaps, interest rate swaps etc. to fulfil client demand
• Trading in financial markets to build strategic positioning for the bank
• Consistently beat benchmark for execution of sterling interest rate swaps.
Stress Testing and Risk Modelling
• Build the internal and external stress tests for RBS which involved significant financial
modelling and often strong programming skills and relational database management.
• Analysed outputs of stress testing to determine best courses of action for the bank, taking
various remediating actions on behalf of the Board to ensure adequate risk profile for the bank.
Digital Disruption in Retail Banking
• Lead contributor to Digital Disruption Working Group on Blockchain and Open Banking
• Presented explanation of Blockchain to the Executive Treasury Committee
• Subject Matter Expert for internal Blockchain projects.
• Contributor to Open Banking forum, Investment Committee, Asset and Liability Committee.
• Led efforts to investigate feasibility of moving the Ring-Fenced Bank Treasury to a cloud-
based operating model
• Managed funding for new digital P2P lending
• Lead member of AI working group for building AI-based tools to forecast relevant retail bank
product usage (e.g. operational deposits, mortgages)
• Oversaw development of all new stress tests, assessed and approved new products and developed models to analyse the risks being run across the firm.
• Developed an enhanced Secured Funding stress model ensuring that the collateral
substitution and credit intermediation risks were being captured.
MSc, Computer Science
Bachelors, Modern History
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