Colan is currently unavailable
Colan Walsh
Verified Expert in Engineering
Software Developer
London, United Kingdom
Toptal member since March 3, 2020
Bio
Colan is an experienced senior financial quantitative developer and researcher with experience across various asset classes and trading venues. He has a multidisciplinary background, working in quant development, quant research, and options trading for multiple investment banks and hedge funds.
Portfolio
AmateMint Labs LLC
Python, Algorithmic Trading, Algorithmic Trading Analysis, Google Cloud...
Umoja Labs Corp.
Financial Modeling, Trading, Quantitative Finance, High-frequency Trading (HFT)...
Hedgix Management Limited
Architecture, Agile, SQL, Databases, Python, Hedge Funds, Assets, Investments...
Experience
- Quantitative Finance - 15 years
- Algorithmic Trading - 15 years
- Options Trading - 14 years
- Derivatives - 13 years
- Python - 10 years
- Data Science - 6 years
- Machine Learning - 5 years
- Crypto - 3 years
Preferred Environment
Jupyter, PyCharm, Scikit-learn, Pandas, Python, Linux, Docker, PostgreSQL, Redis
The most amazing...
...quant research team I've built generated returns of 20-30% (unleveraged) from market-neutral algorithmic crypto trading.
Work Experience
Equity Index Futures Algorithmic Trader
2023 - 2025
AmateMint Labs LLC
- Built a live algorithmic trading platform, architected to be integrated with APIs from multiple futures brokers.
- Developed a high-performance event-based backtesting engine to calibrate and optimize the client's trading strategy.
- Collaborated closely with the client on iterative trading algorithm refinement and optimization of entry and exit levels for high-frequency trading strategy.
Technologies: Python, Algorithmic Trading, Algorithmic Trading Analysis, Google Cloud, API Integration, DevOps, Artificial Intelligence (AI), Predictive Modeling, Predictive Analytics, Entity Relationships, ETL, Machine Learning Operations (MLOps), Regression Modeling, Financial Modeling, Fintech, High-frequency Trading (HFT), Backtesting Trading Strategies, Pine Script, Pandas, Equity Investment, Pairs Trading, Quantitative Mean Reversion, Statistical Modeling
FX and Crypto Options Algorithmic Trader
2023 - 2023
Umoja Labs Corp.
- Developed a Synthetic Options trading algorithm for FX and Crypto markets, used by clients as a lower-cost/capital-intensive alternative to purchasing traditional options.
- Created and managed the trading algorithm behind "yBTC": a BTC-denominated liquid stablecoin, generating annualised returns of 5 to 8%, using liquid trading strategies on centralised and decentralised exchanges.
- Recruited and managed a team of three quant developers, focused on implementing centralised and decentralised exchange connectivity across crypto markets.
Technologies: Financial Modeling, Trading, Quantitative Finance, High-frequency Trading (HFT), Blockchain, Backtesting Trading Strategies, Options Trading, Quantitative Mean Reversion, Statistical Modeling
Financial Engineer and Tech Lead
2023 - 2023
Hedgix Management Limited
- Architected a microservices-based cloud-hosted algorithmic trading platform (OMS/EMS) integrated with ChatGPT API, multiple brokers (e.g., IBKR), and market data services, supporting high-frequency trading and long-term investing strategies.
- Designed a derivatives structuring validation engine, providing validation around complex derivatives structures generated by LLM before execution.
- Prepared a detailed backlog and development estimates for the implementation of the trading architecture and validation engine.
Technologies: Architecture, Agile, SQL, Databases, Python, Hedge Funds, Assets, Investments, MySQL, Banking & Finance, Azure, Derivatives, Microservices, Algorithmic Trading, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, Startups, Factor Analysis, Data Extraction, Data Wrangling, API Integration, DevOps, Artificial Intelligence (AI), Predictive Modeling, Predictive Analytics, Project Management, Entity Relationships, ETL, Generative Pre-trained Transformers (GPT), Machine Learning Operations (MLOps), Regression Modeling, Financial Modeling, Fintech, Backtesting Trading Strategies, Stock Market, Technical Leadership, Pandas, Equity Investment, Quantitative Mean Reversion, Statistical Modeling, Fintech Consultant
Quant Researcher
2022 - 2023
TokenEdge
- Performed large-scale cross-sectional modeling of NFT price time series dynamics, using PCA, across the top 500 collections on the Ethereum blockchain.
- Built a predictive ensemble model for NFT price direction classification, incorporating SGD, KNN, and simple neural networks, among others.
- Set up Google Cloud Platform-based quant research environment, with Docker deployment and GCS for data storage.
- Evaluated various NFT/token market data vendors and built data pipeline integrations with the top choices.
Technologies: Python, Google Cloud Platform (GCP), Linux, Docker, Pandas, Scikit-learn, Matplotlib, Algorithmic Trading, Data Science, Machine Learning, Blockchain, Ethereum, SQLAlchemy, DataFrames, Visual Basic, Exchanges, Digital Asset Management, Stock Exchange, Fractionalization, Protobuf, Asynchronous I/O, Amazon S3 (AWS S3), Agile, Architecture, Assets, Investments, Banking & Finance, Amazon RDS, Algorithmic Trading Analysis, Automated Trading Software, Mathematical Finance, Mathematics, Data Analysis, Data Visualization, Exploratory Data Analysis, Data Scraping, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, Startups, Factor Analysis, Data Extraction, Data Wrangling, API Integration, DevOps, Artificial Intelligence (AI), Predictive Modeling, Predictive Analytics, Non-fungible Tokens (NFT), Web3, Entity Relationships, ETL, Amazon Web Services (AWS), Cryptocurrency, Machine Learning Operations (MLOps), Regression Modeling, Financial Modeling, Fintech, Backtesting Trading Strategies, Binance API, XLSX File Processing, Quantitative Mean Reversion, Statistical Modeling
Senior Quant Researcher and Algorithm Developer
2021 - 2022
SPS Trading
- Recruited and managed a team of remote quant researchers and data scientists focused on crypto algorithmic trading strategies.
- Managed a team focused on generating a portfolio of market-neutral strategies.
- Architected and implemented a Python-based algorithmic trading and backtesting platform designed explicitly for crypto spot and derivatives trading.
Technologies: Python, Crypto, Machine Learning, Algorithmic Trading, Algorithms, Options Trading, Financial APIs, Trading, Financial Markets, Stock Trading, Microservices, Asyncio, Docker, WebSockets, Excel 2016, Data Engineering, Relational Databases, SQL, Git, GitHub, Bitcoin, Bots, Back-end, APIs, Team Leadership, MySQL, Amazon EC2, Amazon Web Services (AWS), Data Science, Databases, Deep Neural Networks (DNNs), Data Reporting, REST, Docker Compose, AWS Lambda, GraphQL, Pytest, REST APIs, Redis, Non-fungible Tokens (NFT), Excel Macros, Finance, AWS Cloud Architecture, Cloud, Arbitrage, Forex, Trading Systems, Multithreading, Financial Market Data, Fixed Income, FX Risk Analysis, gRPC, Computational Finance, Quantitative Finance, Hedge Funds, Data Analysis, Data Visualization, Time Series, Time Series Analysis, Optimization, Linear Optimization, SQLAlchemy, DataFrames, Excel Reporting, Exchanges, Digital Asset Management, Stock Exchange, Protobuf, Asynchronous I/O, CTO, Leadership, Blockchain, Amazon S3 (AWS S3), Flask, Agile, Architecture, Assets, Investments, Banking & Finance, Amazon RDS, Algorithmic Trading Analysis, Automated Trading Software, Mathematical Finance, Mathematics, Exploratory Data Analysis, MQL4, MQL5, MQL, Data Scraping, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, Startups, Factor Analysis, Data Extraction, Data Wrangling, Serverless, API Integration, DevOps, Artificial Intelligence (AI), Predictive Modeling, Predictive Analytics, Web3, Data Build Tool (dbt), Entity Relationships, Snowflake, ETL, Cryptocurrency, Machine Learning Operations (MLOps), Amazon SageMaker, Regression Modeling, Financial Modeling, Fintech, High-frequency Trading (HFT), Backtesting Trading Strategies, Binance API, Technical Leadership, Pine Script, Pandas, XLSX File Processing, Quantitative Mean Reversion, Statistical Modeling
Head of Quant Development and Research
2020 - 2021
Tickup
- Recruited and managed a team of remote quant researchers and data scientists, working on delivering equity trading strategies using alternative datasets.
- Worked with a Stockholm-based data team for onboarding and cleaning complex semi-structured alternative datasets such as Ravenpack (news feeds), ConsumerEdge/Yodlee (credit card data), Apptopia (app downloads), and Estimize (crowd-sourced estimates).
- Led the development of alternative data-based quantitative trading strategies, delivering unleveraged returns of 20-40% per annum in backtesting.
- Served as lead architect for a Python-based algorithmic trading and backtesting platform designed around alternative data and machine learning trading strategies (using Scikit-learn and TensorFlow).
Technologies: Python, Scikit-learn, Linux, Management, Research, Algorithms, Options Trading, Financial APIs, Trading, Financial Markets, Stock Trading, Microservices, Asyncio, Docker, WebSockets, Data Engineering, Relational Databases, SQL, Git, GitHub, Bitcoin, Bots, Back-end, APIs, Team Leadership, MySQL, Amazon EC2, Amazon Web Services (AWS), Data Science, Databases, Deep Neural Networks (DNNs), Data Reporting, REST, Docker Compose, Pytest, REST APIs, PostgreSQL, Redis, Finance, Interactive Brokers API, AWS Cloud Architecture, Machine Learning, Cloud, Arbitrage, Forex, Trading Systems, Multithreading, Financial Market Data, Fixed Income, FX Risk Analysis, Computational Finance, Quantitative Finance, Hedge Funds, Data Analysis, Data Visualization, Time Series, Time Series Analysis, Optimization, Linear Optimization, SQLAlchemy, DataFrames, Amazon RDS, Exchanges, Digital Asset Management, Stock Exchange, Asynchronous I/O, CTO, Leadership, Blockchain, Flask, Agile, Architecture, Assets, Investments, Banking & Finance, Algorithmic Trading Analysis, Automated Trading Software, Mathematical Finance, Mathematics, Exploratory Data Analysis, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, Startups, Factor Analysis, Data Wrangling, FIX Protocol, DevOps, Artificial Intelligence (AI), Predictive Modeling, Predictive Analytics, Project Management, Non-fungible Tokens (NFT), Web3, Entity Relationships, ETL, Apache Airflow, Cryptocurrency, Machine Learning Operations (MLOps), Regression Modeling, Financial Modeling, Fintech, High-frequency Trading (HFT), Backtesting Trading Strategies, Stock Market, Binance API, Technical Leadership, Pandas, XLSX File Processing, Equity Investment, Quantitative Mean Reversion, Statistical Modeling
Freelance Python Quant Researcher and Developer
2018 - 2020
Achilleon Consulting
- Created an algorithmic trading platform expressly designed to handle machine learning based trading strategies. The platform incorporates multi-threaded/asynchronous architecture, handling multiple data sources and trading venues simultaneously.
- Implemented a machine learning (neural network) model for derivatives pricing, using Scikit-learn and TensorFlow, with hyperparameter optimization using Scikit-optimize.
- Designed and implemented a standardized REST API for market data retrieval and transformation from multiple heterogeneous data sources. Built wrappers for Bloomberg, Reuters Eikon, IBKR, Quandl, Oanda, and FXCM.
- Coded risk and P&L calculation tools for a long-short equity hedge fund, incorporating an Excel/VBA front end and a Python back end connected via xlwings.
- Implemented an event screener framework for a long-short equity hedge fund to streamline the management of event-based trading.
- Created an equity trading strategy simulator, incorporating what-if, optimization tools, and trade event visualizations.
- Designed and trained machine learning models for equity trading to assist with momentum trading (especially entry and exit timing) and to optimize trailing stop implementation.
- Created model for cross-market equity beta decomposition via unsupervised learning (Scikit-learn).
- Coded a trading strategy optimization framework for VIX trading for a volatility trading hedge fund.
Technologies: Reuters Eikon, Bloomberg, Excel VBA, TensorFlow, Scikit-learn, xlwings, Django, Flask, Pandas, NumPy, Python, Algorithms, Options Trading, Financial APIs, Trading, Financial Markets, Stock Trading, Microservices, Asyncio, Docker, WebSockets, Excel 2016, Data Engineering, Django REST Framework, Relational Databases, SQL, Git, GitHub, Bitcoin, Bots, Back-end, APIs, Team Leadership, Amazon EC2, Amazon Web Services (AWS), Microsoft Excel, Data Science, Databases, Deep Neural Networks (DNNs), Data Reporting, REST, Docker Compose, Pytest, REST APIs, PostgreSQL, Redis, Excel Macros, Finance, Interactive Brokers API, AWS Cloud Architecture, Machine Learning, Cloud, Arbitrage, Trading Systems, Multithreading, Financial Market Data, Fixed Income, FX Risk Analysis, Computational Finance, Quantitative Finance, Hedge Funds, Data Analysis, Data Visualization, Time Series, Time Series Analysis, Optimization, Linear Optimization, SQLAlchemy, DataFrames, Visual Basic, Excel Reporting, Amazon RDS, Exchanges, Stock Exchange, Asynchronous I/O, Blockchain, Amazon S3 (AWS S3), Agile, Architecture, Assets, Investments, Banking & Finance, Algorithmic Trading Analysis, Automated Trading Software, Mathematical Finance, Mathematics, Exploratory Data Analysis, MQL4, MQL5, MQL, Data Scraping, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, Startups, Data Extraction, Data Wrangling, FIX Protocol, DevOps, Artificial Intelligence (AI), Predictive Modeling, Predictive Analytics, Entity Relationships, ETL, Cryptocurrency, Regression Modeling, Financial Modeling, Fintech, Currency Exchange, High-frequency Trading (HFT), Stock Market, XLSX File Processing, Equity Investment, Pairs Trading, Quantitative Mean Reversion, Statistical Modeling, Fintech Consultant
Rate Derivatives Desk Quant
2016 - 2018
Nomura
- Fully refactored risk and P&L tools for swaptions trading in London and New York, covering EUR, USD, and GBP. Included overhaul of scenario generation, and generation of real-time risks intraday.
- Fully refactored risk, P&L, pricing tools, for inflation derivatives (EUR, GBP, USD), covering inflation swaps, bonds, options. Included refinement of inflation RV trade screening tools.
- Refactored position monitoring and pricing tools for STIRT and FX Forward trading desk in London and New York. Included configuring price publication to downstream customer-facing systems via Tibco bus.
- Coded an optimum vega hedging algorithm for swaptions trading, identifying the best P&L hedging trades given an input vega grid.
- Refactored curve and volatility surface builders for swaptions and inflation options.
- Built a PCA-based framework for alternative rates delta/gamma risk and P&L explanation.
Technologies: Reuters Eikon, Bloomberg, Analytics, Excel VBA, Python, Algorithms, Options Trading, Financial APIs, Trading, Financial Markets, Excel 2016, Data Engineering, Relational Databases, SQL, Microsoft Excel, Data Science, Databases, Data Reporting, REST, REST APIs, Jira, Excel Macros, Finance, Arbitrage, Trading Systems, Financial Market Data, Fixed Income, Computational Finance, Quantitative Finance, Data Analysis, Time Series, Time Series Analysis, Optimization, Linear Optimization, DataFrames, Power Query, Excel Reporting, Exchanges, Stock Exchange, Fractionalization, Assets, Investments, Banking & Finance, Mathematical Finance, Mathematics, Exploratory Data Analysis, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, FIX Protocol, Predictive Modeling, Predictive Analytics, Entity Relationships, ETL, Regression Modeling, Financial Modeling, Fintech, XLSX File Processing, Pairs Trading, Quantitative Mean Reversion, Statistical Modeling
Rate Derivatives Quant Trader
2015 - 2016
Caxton Associates
- Executed derivatives trades (exchange and OTC) on behalf of portfolio manager with $500 million AUM; fed funds futures, eurodollar/euribor futures, FRAs, OIS, swaps, and basis.
- Developed portfolio risk and P&L calculation tool, using ALIB quant analytics. Included position and market data retrieval, risk & P&L calculation. Capable of retroactively generating risk/P&L for any past date.
- Created market data retrieval/processing/storage framework, sourcing data from third-party APIs: Bloomberg, BAML, JPM, Citi, and Barclays.
- Coded relative-value market monitor for spot and forward swap and basis rates; including the charting of historic rolldown/carry/range/correlation.
- Built "short-end" market monitor: a live and historic analysis tool for Libor and OIS futures/swaps; including Libor/basis predictive analytics.
- Created a dashboard tool to display results of various econometric/technical analyses, continuously updated from Bloomberg/Haver DLX. For example, bund scarcity analysis, MACD-based TY price tracking, 5y5y equilibrium modeling.
- Created a knowledgebase tool: hashtag-based PDF/text research organizing framework, integrated with multiple other tools (e.g. SignalMonitor, Dashboard).
- Created the SignalMonitor tool: realtime monitoring of market data levels (or any arbitrary function of levels) for trade entry/exit signals, with email/desktop/text alerts. Integrated with KnowledgeBase to automatically send appropriate research.
Technologies: Adobe, FINCAD, Bloomberg, Excel VBA, VBScript, Python, Algorithms, Options Trading, Financial APIs, Trading, Financial Markets, Excel 2016, Relational Databases, SQL, Microsoft Excel, Databases, Data Reporting, REST APIs, Excel Macros, Finance, Arbitrage, Trading Systems, Financial Market Data, Fixed Income, Computational Finance, Quantitative Finance, Hedge Funds, Data Analysis, Time Series, Time Series Analysis, Optimization, Linear Optimization, Power Query, Excel Reporting, Exchanges, Stock Exchange, Assets, Investments, Banking & Finance, Mathematical Finance, Mathematics, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, Predictive Modeling, Predictive Analytics, ETL, Regression Modeling, Financial Modeling, Fintech, XLSX File Processing, Bloomberg API, Pairs Trading, Quantitative Mean Reversion, Statistical Modeling
Derivatives Quant Trader
2012 - 2015
Royal Bank of Scotland
- Contributed as part of a two-person trading team involved in the creation of a new trading desk to algorithmically market-make exchange-traded bond options, including dynamic-VAR-based automated hedging, and on-the-fly SABR volatility surface calibration.
- Implemented technology platform for RBS Strategic Hedging program, to reduce bank-wide RWA/SVAR using vanilla options to hedge tail risk, including designing the algorithms to solve for optimal RWA-reducing vanilla options hedges.
- Risk-managed the FX/Rates Hybrid Derivatives trading portfolio, including calculation and hedging of FX/Rates Delta/Gamma/Vega, using options, futures, swaps, and FX. It also included involved and executing customer requests for exotic derivatives.
- Managed algorithmic FX/Rates cross gamma hedging algorithms for the Hybrids portfolio using the RBS Agile algorithmic trading platform.
- Managed NPV valuations for portfolio auctions to other banks (PRDCs, TEC10 CMTs, structured notes). This also included driving risk compressions for a large portfolio of long-dated FX options.
- Worked closely with Dynamic Strategies desk on VAR-based algorithmic hedging framework for custom index options.
- Developed trading strategy backtesting engine, used to discover and optimize trading strategies for the Dynamic Strategies (Custom Index) trading desk.
Technologies: XML, R, Excel VBA, Visual Basic, Reuters Eikon, Bloomberg, Algorithmic Trading, Libraries, Analytics, Algorithms, Options Trading, Financial APIs, Trading, Financial Markets, Stock Trading, Excel 2016, Data Engineering, Relational Databases, SQL, Microsoft Excel, Databases, Data Reporting, Excel Macros, Finance, Arbitrage, Forex, Trading Systems, Financial Market Data, Fixed Income, FX Risk Analysis, Computational Finance, Quantitative Finance, Data Analysis, Time Series, Time Series Analysis, Linear Optimization, Power Query, Excel Reporting, Exchanges, Stock Exchange, Fractionalization, Leadership, Assets, Investments, Banking & Finance, Mathematical Finance, Mathematics, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, Predictive Modeling, Predictive Analytics, ETL, Regression Modeling, Financial Modeling, Fintech, Currency Exchange, XLSX File Processing, Bloomberg API, Quantitative Mean Reversion, Statistical Modeling
FX and Rates Derivatives Desk Quant
2010 - 2012
Royal Bank of Scotland
- Completely refactored legacy risk and P&L management tools for FX/IR hybrid derivatives (including long-dated FX options), covering traders in London, New York, and Tokyo, and reducing the start-of-day process from two hours (in Tokyo) to 30 seconds.
- Implemented a new FX and Rates cross-gamma scenario analysis toolkit, covering six rate curves and volatility surfaces and ten FX forward curves and volatility surfaces.
- Contributed to the "RBS Agile" algorithmic platform to implement automated hedging for FX and Rates cross-gamma.
- Created an Excel VBA-based risk aggregation framework, used by six trading desks across the bank, which provided PV/risk/scenario aggregation or drill down to individual trade levels.
- Coded an Excel add-in used extensively across the Royal Bank of Scotland, containing utility array manipulation functions.
- Developed and improved curve-building tools: FX-forwards; swaps; bond, funding, and credit spreads; CMS/CMT cross-currency adjusted discounting; equity dividends; and correlation term-structure.
- Revised volatility surface building tools for swaptions, cap floors, FX options, equity, and commodity index primarily using SABR, and incorporating implied vol event-weighting.
- Built a set of tools to publish structured note prices to Reuters and Bloomberg, used by several trading desks across the Royal Bank of Scotland.
- Created a trading strategy simulation engine, used for custom index strategy research.
- Implemented the "Generic Position Sheet," an automatically configurable risk management tool that could be used transparently by any trading desk in the bank.
Technologies: XML, Excel VBA, Visual Basic, Reuters Eikon, Bloomberg, Algorithmic Trading, Libraries, Analytics, Algorithms, Options Trading, Financial APIs, Trading, Financial Markets, Excel 2016, Data Engineering, Relational Databases, SQL, Microsoft Excel, Databases, Data Reporting, REST APIs, Jira, Excel Macros, Finance, Arbitrage, Forex, Trading Systems, Financial Market Data, Fixed Income, FX Risk Analysis, Computational Finance, Quantitative Finance, Data Analysis, Time Series, Time Series Analysis, Linear Optimization, Power Query, Excel Reporting, Exchanges, Stock Exchange, Fractionalization, Assets, Investments, Banking & Finance, Mathematical Finance, Mathematics, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, Predictive Modeling, Predictive Analytics, Entity Relationships, ETL, Regression Modeling, Financial Modeling, Fintech, Currency Exchange, XLSX File Processing, Bloomberg API, Quantitative Mean Reversion, Statistical Modeling
Exotic Rates and FX Derivatives Quant Developer
2008 - 2010
Credit Suisse
- Maintained 12 complex trading risk and position workbooks, built on the Credit Suisse GMAG quant library, covering inflation, exotic rates, rate/FX hybrids, commodity/FX hybrids, and counterparty credit risk.
- Migrated numerous VBA-based risk scenario generation algorithms to a COM-based analytics framework, allowing overnight scenario risk calculations to run in parallel on server farms.
- Rolled out new interest rate curve models for 12 currencies across two business areas. A highly complex project, requiring very close co-operation with the quant group, trading, product control and risk control, and other IT groups.
- Created a complete set of new trading tools for Inflation trading portfolio; including risk and position tools; P&L decomposition tools, market data publication tools; risk scenario design.
Technologies: Shell Scripting, Excel VBA, Visual Basic, Libraries, Analytics, Algorithms, Options Trading, Financial APIs, Trading, Financial Markets, Excel 2016, Data Engineering, Relational Databases, SQL, Microsoft Excel, Databases, Data Reporting, Jira, Finance, Arbitrage, Forex, Trading Systems, Financial Market Data, Fixed Income, FX Risk Analysis, Computational Finance, Quantitative Finance, Data Analysis, Time Series, Time Series Analysis, Linear Optimization, Power Query, Excel Reporting, Exchanges, Stock Exchange, Assets, Investments, Banking & Finance, Mathematical Finance, Mathematics, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, FIX Protocol, Predictive Modeling, Predictive Analytics, Entity Relationships, ETL, Regression Modeling, Financial Modeling, Fintech, Currency Exchange, XLSX File Processing, Bloomberg API, Quantitative Mean Reversion, Statistical Modeling
Experience
Algo Trading Platform for Machine Learning Trading Strategies
The project involved creating an algorithmic trading platform expressly designed to handle machine learning-based trading strategies. The platform incorporates multi-threading, multi-processing and asynchronous architecture, and is capable of running large numbers of independent strategies, and handling multiple data sources and trading venues simultaneously. The platform is accessible by front-end applications via a REST API (using Flask).
Neural Network Approximation of Derivatives Pricing Models
The project involved replication of existing vanilla derivatives pricing models with densely-connected neural networks (DNNs). The machine learning stack used was Scikit-Learn and Tensorflow, with hyperparameter optimization using Scikit-Optimize.
Standardized REST API for Heterogenous Market Data Sources
The project involved designing a single standard REST API specification to cover a range of market data sources, with varying requests and return formats: Bloomberg, Reuters Eikon, IBKR, Quandl, Oanda, and FXCM. Wrappers were built around the native APIs for these data sources, allowing significant removing complexity to be removed from downstream systems.
Equity Market Beta Decomposition Model
The objective of this project was to use unsupervised learning techniques (using Scikit-Learn) to allow identification and removal of both general market beta, and automated identification of equity clusters (groups of highly correlated stocks). This work was undertaken for an equity long-short hedge fund.
Optimum Vega Hedging Tool
This project was undertaken for a swaptions trading desk at an investment bank.
The tool allowed a trading desk to identify the best maturity/expiries to trade to minimize P&L volatility, given an input vega grid, and taking into account historical correlations across the volatility surface.
The tool allowed a trading desk to identify the best maturity/expiries to trade to minimize P&L volatility, given an input vega grid, and taking into account historical correlations across the volatility surface.
Signal Monitor Tool for Real-Time Market Signal Notifications
This was created for a macro hedge fund. The SignalMonitor tool allowed realtime monitoring of market data levels (or any arbitrarily complex function of those levels) for specific thresholds e.g. for trade entry/exit signals. The tool generated email/desktop/text alerts and was integrated with a hashtag-driven knowledge base such that appropriate research would be automatically sent with the alert.
RWA Reduction Trading Platform
I was a quant trader on the new "Strategic Hedging" trading desk, whose purpose was to reduce bank-wide RWA/SVAR using vanilla options to hedge tail risk. I built the technology platform from the ground up, including designing the algorithms to solve for optimal RWA-reducing vanilla options hedges.
FX & Rates Exotic Derivatives Cross Gamma Toolkit
This project involved working with scenario generation results from multiple risk engines, delivered unreliably, and in an inconsistent format, to a risk database. The toolkit had to deal with missing or incorrect scenario results, the transformation of scenario results in a consistent format, and aggregation for display purposes. The cross-gamma coverage was 6 rate curves and SABR volatility surfaces, and 10 FX forward curves and SABR volatility surfaces.
Derivatives Risk Aggregation Toolkit
Created an Excel VBA-based risk aggregation framework, used by six trading desks across the bank, which provided PV/risk/scenario aggregation or drill down to individual trade level. It also allowed design and sharing of standardised reports, and batch delivery of reports to risk management sheets.
Education
2006 - 2007
Master's Degree in Mathematical Finance
London School of Economics - London, England, UK
2002 - 2005
Bachelor's Degree (First Class Honors) in Economics and International Politics
University of Wales - Aberystwyth, Wales, UK
Certifications
JULY 2018 - PRESENT
Tensorflow for Deep Learning
Udemy
MARCH 2015 - PRESENT
Oracle Certified Associate, Java SE8
Oracle
FEBRUARY 2013 - PRESENT
Exchange Trader Examination
Eurex
NOVEMBER 2012 - PRESENT
CISI Level 3 Certificate in Derivatives
Chartered Institute for Securities & Investment
MAY 2012 - PRESENT
Certificate in Quantitative Finance
CQF Institute
SEPTEMBER 2001 - PRESENT
Professional Certificate in Management
Open University
Skills
Libraries/APIs
NumPy, Pandas, Scikit-learn, Bloomberg API, Interactive Brokers API, Binance API, TensorFlow, REST APIs, Python Asyncio, Asyncio, SQLAlchemy, Quandl API, Matplotlib, SciPy, Keras, Protobuf
Tools
Jupyter, Reuters Eikon, Excel 2016, Microsoft Excel, Bloomberg, TensorBoard, PyCharm, IPython, Microsoft Access, Celery, Power Query, FINCAD, Adobe, Git, GitHub, MD5, Slack, Docker Compose, Pytest, Jira, Apache Airflow, Amazon SageMaker
Languages
Excel VBA, SQL, Python, Visual Basic for Applications (VBA), VBScript, Visual Basic, XML, MQL4, MQL5, MQL, Java, R, GraphQL, Snowflake, Pine Script
Paradigms
Agile, Functional Programming, Object-oriented Programming (OOP), Agile Project Management, Quantitative Research, Microservices, Asynchronous Programming, Concurrent Programming, REST, ETL, Scrum, Test-driven Development (TDD), Management, DevOps
Platforms
Jupyter Notebook, Amazon Web Services (AWS), Docker, Blockchain, Ubuntu, Heroku, Linux, Amazon EC2, Google Cloud Platform (GCP), Ethereum, Azure, AWS Lambda
Industry Expertise
Trading Systems, Banking & Finance, Project Management, High-frequency Trading (HFT)
Storage
JSON, Databases, MySQL, Amazon S3 (AWS S3), Relational Databases, PostgreSQL, Redis, Google Cloud
Frameworks
Flask, Django, Django REST Framework, gRPC
Other
FX, Interest Rate Risk, Interest Rate Swaps, Fixed-income Derivatives, Derivatives, Options Trading, Trading Applications, Cross-currency Swaps, Swaps, Bonds, Futures, Options Theory, Option Pricing, Risk Models, Market Risk, Support Vector Machines (SVM), Decision Trees, Random Forests, Volatility, Portfolio Optimization, Mathematical Finance, Algorithmic Trading, Algorithmic Trading Analysis, Foreign Exchange (FX) Hedging, FX Risk Analysis, Quantitative Finance, Financial Market Data, Fixed Income, Multithreading, Data Science, Artificial Intelligence (AI), Machine Learning, IT Project Management, Fintech, Algorithms, Financial APIs, Trading, Financial Markets, Stock Trading, Stock Market, Excel Expert, Bots, Back-end, APIs, Non-fungible Tokens (NFT), Arbitrage, Forex, Data Analysis, Excel Macros, Finance, Computational Finance, Hedge Funds, Data Visualization, Time Series, Time Series Analysis, Optimization, Linear Optimization, DataFrames, Excel Reporting, Exchanges, Digital Asset Management, Stock Exchange, Leadership, Architecture, Assets, Investments, Automated Trading Software, Mathematics, Monte Carlo Simulations, Exploratory Data Analysis, Data Scraping, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, Factor Analysis, Data Extraction, Data Wrangling, API Integration, Predictive Modeling, Regression Modeling, Financial Modeling, Currency Exchange, Backtesting Trading Strategies, Regression, Technical Leadership, XLSX File Processing, Trading Bots, Options, Quantitative Analysis, Forex Trading, Equity Investment, Pairs Trading, Quantitative Mean Reversion, Statistical Modeling, Fintech Consultant, xlwings, Principal Component Analysis (PCA), Neural Networks, Pricing Models, Finance APIs, Processing & Threading, Macroeconomics, Economics, RESTful Microservices, Statistics, Deep Learning, Supervised Learning, Data Engineering, Crypto, Cryptocurrency, Decentralized Finance (DeFi), Bitcoin, Team Leadership, Deep Neural Networks (DNNs), Data Reporting, AWS Cloud Architecture, Cloud, Fractionalization, Asynchronous I/O, CTO, Startups, Probability Theory, Predictive Analytics, Web3, Data Build Tool (dbt), Entity Relationships, Machine Learning Operations (MLOps), Binary Option Trading, Analytics, Libraries, Shell Scripting, Systematic Trading, Commodity Markets, Credit Risk, Unsupervised Learning, WebSockets, Research, Econometrics, Politics, Amazon RDS, Serverless, FIX Protocol, Generative Pre-trained Transformers (GPT)
Collaboration That Works
How to Work with Toptal
Toptal matches you directly with global industry experts from our network in hours—not weeks or months.
1
Share your needs
Discuss your requirements and refine your scope in a call with a Toptal domain expert.
2
Choose your talent
Get a short list of expertly matched talent within 24 hours to review, interview, and choose from.
3
Start your risk-free talent trial
Work with your chosen talent on a trial basis for up to two weeks. Pay only if you decide to hire them.
Top talent is in high demand.
Start hiring