Career Profile

Specializing in Quantitative Research, Risk Models, Digital Assets, and Quantitative Analytics, I am a seasoned quantitative researcher and data scientist with a deep-rooted background in the digital asset and DeFi sectors. My professional journey includes pivotal roles at leading firms like Cloudwall, Quant Island, Memento Blockchain, and The StatPro Group. My expertise lies in the adept design and implementation of sophisticated risk models — including market, liquidity, and credit risk. I have a proven track record of collaborating with both academia and industry partners, delivering production-grade code and analytics solutions in the finance sector. Additionally, I have leveraged my knowledge and experience to educate others, holding lecturer positions and conducting both in-person and web-based training sessions on advanced quantitative finance topics.


Chief Scientist

2024 -- Present
Cloudwall, Singapore

As the leader of the research group at Cloudwall, my responsibilities encompass:

  • Directing strategic development in quantitative research and ensuring the alignment of research outputs with evolving client needs, particularly in the digital asset domain.
  • Guaranteeing the accuracy and reliability of our analytics and data services.
  • Fostering a culture of continuous learning and innovation within the team, while also mentoring team members to enhance their professional growth.
  • Overseeing project management aspects, including the creation and assignment of JIRA tickets and optimization of go-to-production plans to ensure timely project delivery.

Senior Quant Research Engineer

2023 -- Jan. 2024
Cloudwall, Singapore

In this role, I:

  • Played a pivotal role in the design, prototyping, and implementation of advanced risk models (market, liquidity, credit, and operational) using various quantitative methods including factor analysis, simulations, and agent-based systems.
  • Significantly improved code quality in the research group by implementing quantitative measures like the PyLint score and the Mypy score.
  • Streamlined the data interface between the quantitative library and data acquisition module.
  • Leveraged large language models to triple code-writing efficiency.
  • Designed and implemented cutting-edge risk models for the core library, accelerating their deployment to production within months.
  • Actively coached junior members, fostering knowledge sharing across the organization.

Chief Quantitative Analyst

2013 -- Present
Quant Island Pte. Ltd, Singapore

My tenure here includes:

  • Extensive consultancy in both traditional and digital finance, with a recent focus on assessing various risk types (market, interest rate, liquidity) for a digital exchange.
  • Contributing to Quant Island’s reputation as a fintech-certified quantitative finance consulting firm in Singapore.

Protocol Scientist

2019 -- 2022
Memento Blockchain Pte. Ltd., Singapore

In this role, I:

  • Led the DeFi protocol development for the DOMANI project, overseeing smart contract creation and analytics.
  • Specialized in building decentralized Digital Asset Management solutions on both Algorand and Ethereum blockchains.
  • Established collaborations with prominent DeFi projects including Uniswap, Opyn, UMA, SetProtocol, AAVE, and Compound.
  • Expertly developed and deployed Solidity smart contracts using Truffle and Hardhat tools.
  • Utilized Reach and PyTeal languages to create formally verified Dapps on the Algorand blockchain, enhancing security and reliability.

Data Scientist

2018 -- 2019
Poseidon, Malta

Applied data-science techniques and quantitative finance to the field of Tokenized Carbon Credits on the Stellar blockchain.


2018 -- 2019
ESSEC Business School, Singapore

My key contributions included:

  • Pioneering the application of data science and quantitative finance methodologies in the realm of Tokenized Carbon Credits.
  • Leveraging the Stellar blockchain to enhance the efficacy and transparency of carbon credit transactions.

Chief Analytics Officer

2016 -- 2019
Hottab, Hanoi (Vietnam) and Singapore

Was responsible for the company’s data-science team and the research and development of the hospitality analytics. Models included advanced use of python/numpy/pandas/scipy

Chief Research Advisor

2013 —- 2018
The StatPro Group, Worldwide
  • Cooperated with the quantitative-research team to create original and innovative research in the field of liquidity risk (especially applied to the bond market) and other financial topics.
  • Independently carried out model validations for pricing functions and risk analytics.
  • Performed in-person and web training on advanced topics in quantitative analytics: risk modeling, fundamentals of derivative pricing, fixed-income attribution for both performance and risk.

Adjunct Professor

2010 -- 2014
Università degli Studi di Milano-Bicocca, Milan, Italy
  • Lectured Interest-Rate Derivatives (providing 5 course credits) for the Advanced Derivatives class of the Master’s Program in Economics and Finance (Laurea Magistrale in Economia e Finanza).
  • Served as thesis advisor for master and Ph.D. students. (Note that the Ph.D. student later became a University professor)

Head of Quantitative Research

2010 -- 2013
StatPro, Milan, Italy
  • Managed the quantitative research group of StatPro; the cutting-edge innovation arm of the whole company.
  • Liaised with universities and the academic world to maintain the highest quality for the StatPro analytics.
  • Was responsible for the creation of new models for pricing functions, risk analytics, and performance measurements.
  • Was responsible for the validation of quantitative models used by the StatPro analytics (including StatPro Revolution).
  • Conducted training on quantitative finance both internally for StatPro personnel, and externally for clients.
  • Supervised the maintenance and the documentation of a library with over two hundred pricing functions.

Head of the Quantitative Analysis Group

2006 -- 2010
StatPro, Milan, Italy
  • Bullet point
  • Managed the quantitative-analysis group that performed R&D of pricing functions and risk analytics.
  • Was responsible for the overall quality of prices and risk figures computed by the StatPro suite.
  • Conducted the internal and external training on quantitative finance.

Head of Risk Development

2003 -- 2006
StatPro, Milan, Italy
  • Managed a group of financial engineers, software developers, and software architects in developing and maintaining the StatPro Risk Suite: Risk API (SRM API), Risk Service (SRS), StatPro Pricing Library (SPL), Risk Management Product (SRM).
  • Conducted research on pricing models and risk management applications.
  • Collaborated with other development groups of StatPro worldwide.

Quant Developer

2000 -- 2003
StatPro Italia, Milan, Italy
  • Cofounded RiskMap, a risk-management software firm.
  • Researched and developed the software, the database, and the risk engine used by the RiskMap suite.
  • Was one of the three cofounders of QuantLib, the leading open-source project for quantitative finance.

Research Associate (Postdoc)

1998 -- 2000
City College of New York, New York City, USA
  • Conducted original research in computational fluid dynamics.
  • Developed a software to evaluate the particle diffusivity of suspensions using Monte Carlo simulations. Advisor: Andreas Acrivos.


A selected list of projects and achievements

Blockchains, Smart Contracts, Decentralized Finance and Dapps
  • Instrumental in creating the DEXTF protocol model for Decentralized Asset Management, from the design stage, to mainnet deployment on the Ethereum blockchain. The project was able to receive two separate grants from the Singapore MAS resulting in funding of more than 400,000 USD.
  • Instrumental in the design of the tokenomics, and deployed the DEXTF token on the mainnet. The DEXTF token at one point was traded at 4USD with a total supply of 100,000,000.
  • Deployed the UMA -DEXTF-$ which provided weekly income in excess of 10,000 USD/week.
  • Developed a DEXTF prototype on the Algorand blockchain that resulted in a grant of 150,000 USD.
  • Currently working on various DeFi projects, including the use of the blockchain-independent Reach Dapp language which ensures formal verification of smart contracts.
Data Science, Quantitative Finance, And Risk Management
  • Created a model to measure the market risk of a centralized/decentralized exchange with focus on the long/short positions.
  • Experienced risk-management quant with a focus on numerical risk simulations.
  • Created original quantitative models to numerically compute risk measures, risk contributions, stress tests, sensitivity analysis, and liquidity risk (liquidity score and market impact).
  • Oversaw the software implementation of quantitative models in software (StatPro Risk Factory) and their link with market data.
  • Designed and implemented the risk engine currently used by the StatPro analytics (StatPro Risk API used by Revolution).
  • Created several robot-trading portfolio to take advantage of certain statistical-arbitrage opportunities in the crypto-currency markets.
  • Revised and improved a model for the computation of the time-to-liquidate and the market impact of bonds, in compliance with US regulation.
  • In the early stages of the COVID19 pandemic, created a model that was able to predicts the early peaks of the virus diffusion in both Singapore and many Italian regions.
  • Created a quantitative model for the distribution of arrivals of restaurant customers by weekday and time, factorizing important independent drivers.
  • Created a general framework to consistently compute performance and risk contributions. The framework generalizes the standard-market method and provides an elegant split of risk contributions using accounting base, that can be chosen to match the performance contributions, and a statistical base.
  • Created an innovative model to compute the Standard Risk Measure mandatory for superannuation funds in Australia.
  • Created a market-factor performance contribution model to split portfolio performance in components coming from identifiable market factors (credit, equity, interest rates, and so on).
  • Created a factor risk decomposition method applicable to most type of simulations (Monte Carlo or historical). This method allows the computation of, for example, the risk contribution in a convertible bond attributable to interest rates, credit risk, or equity risk, respectively. The model has been used in production for more than 8 years.
  • Created a liquidity-risk framework to compute the market bid/ask spread induced by the bid/ask spread of the underlying risk factors.
  • Created a model to simulate the market expectation of credit risk in the historical-simulation method, using the latest credit-default-swap quotes.
  • Created a modification of the Kalotay-Fabozzi model allowing the stability of risk-figures for mortgage-backed securities.
Quantitative Analysis, Model Validation, Bond Pricing and Derivative Pricing
  • A novel technique, the Helena model, to compute the current market trends using trading data at multiple time scales.
  • The creation of a fast quantitative model to estimate the price of subordinated fixed-to-floater convertible bonds (e.g., perpetual fixed-to-floater bonds).
  • Pricing of exotic equity derivatives (e.g., bonds with embedded exotic options).
  • Validation of models used by clients to internally evaluate exotic-instrument value.
  • A unique price-challenge process for complex-asset pricing: this process allows to reproduce exactly on a spreadsheet the same results obtained with a super-cluster computer.
  • Bootstrap, interpolation, and extrapolation of smiled implied-volatility surfaces for equities and foreign-exchange rates.
  • Solving partial-differential equations (PDE) with multiple methods: semi-analytic methods (asymptotic methods), Monte Carlo simulations, multi-pole expansion, finite differences, finite elements, fast Fourier transform, and other spectral methods.
  • Pricing of portfolio credit derivatives such as CDO and first-to-default baskets.
Teaching Quantitative Finance

Experience in teaching quantitative finance includes:

  • The creation of line of lectures, based on the QuantLib library, very effective in presenting the basic concepts of quantitative finance in a natural language.
  • The mastering of an original spreadsheet-presentation technique (as opposed to the common slide presentation) to enhance the audience’s understanding of complex topics.
  • Created a new technique where Jupyter (python) notebooks are used intereactively during the lecture
Team Leadership and Project Management
  • Experienced in managing complex projects with stake-holders from different teams and backgrounds.
  • Ability to gain efficiency by advocating teamwork, inspiring and motivating collaboration.
  • Interfacing and mediating between the business management and the technical team; translating business requirements into working implementations.
  • Ability to manage top-skilled, Ph.D. level, personnel: their expectations and motivations.
Technology, Software Design and Development
  • Created multiple quantitative dashboards using the holoviz-panel framework
  • Created may API using the (python) FastAPI framework
  • Instrumental in creating one of the most sophisticated risk-management softwares/services available on the market (currently operated by the confluence group).
  • Experienced in the implementation of numerical software for derivative pricing and risk management, and the choice of the most appropriate technology.
  • Coordinated the evolution and merging of diverse legacy software and developing teams.
  • Expert in lean software development where the delivery of good-quality maintainable software takes the precedence.
  • Well-versed with test-driven development, continuous delivery, and continuous integration. Responsible for handling the versioning system and the release-management workflow.
  • Designed and administered several relational databases.
  • Experienced with object-oriented and JSON databases. Worked on several projects where a multi-tier distribute architecture was the key ingredient to success.
  • Experienced with web technology and decentralized servers (e.g. more servers in different continents working together).
  • Managing different teams’ programming styles such as extreme programming and agile programming.
  • Creator of a multi-tier RESTful-API based web apps both exposing financial data and for restaurant analytics.
  • Experience with environments for distributed objects such as CORBA, COM, and .NET
  • Parallel programming both in fluid dynamics and finance on multi-processors and computer clusters.
  • Knowledge of different coding techniques such as object-oriented programming, modular programing, and functional programming.
  • Programming languages used: C++, C, Python, Ruby, Fortran, Visual Basic (including advanced Excel programming), SWIG, Perl, tcsh, Mathematica, and many others.
  • Operating systems used: MS-Windows, Unix, Linux, Free BSD, VMS, MacOs (formerly OS X), Aegis (Apollo), SGI Iris, iOS, Android, Symbian, and others.
  • Database servers: SQL-Lite, MS-SQL server, PostgreSQL, MySQL, MariaDB, and ZODB.
  • Development of smartphone apps on the Symbian platform using the python language.
  • Designed, developed, and deployed several projects linking external data from data provider to the internal database.
  • Worked with the following protocols and standards: HTML, XML, RelaxNG, Java Script, and SOAP.
  • Experience with Apache web server, Zope,/Plone, and Ruby on Rails.

OSS Contributions

Open-source contributions

QuantLib - Co-launched the most-popular open-source C++ library in quantitative finance: The QuantLib Project (currently retired senior developer of QuantLib) in November 2000

Thesis and Dissertation Advisor

The full-length thesis are available upon request.

  • Alex Molteni, master candidate
  • Graduated summa cum laude (110 e lode)
    Performance attribution for a portfolio of linear commodity derivatives
  • Andrea Boschetto, master candidate
  • Graduated summa cum laude (110 e lode)
    Risk attribution for linear commodity derivatives
  • Leonardo D’Auria, master candidate
  • Graduated summa cum laude (110 e lode)
    Historical-simulation model for VIX derivatives
  • Edit Rroji, Ph.D. candidate (currently full professor)
  • Graduated with honors
    Risk attribution and semi-heavy tailed distributions

    Skills & Proficiency

    Quantitative Risk Modeling

    Python | Pandas | NumPy

    Quantitative Software Development

    Blockchain and Smart Contracts

    Trading models and bots

    PyTeal and Solidity