Work with Arthur
About
Arthur’s AI for Finance Qualifications
Experience level: Director
I'm a physicist by training (Ph.D., University of Pennsylvania) who has spent about twenty years building models that financial institutions actually rely on. At Western Asset I built machine-learning models for fixed-income risk that held above 99% accuracy out of sample, and an NLP tool that cut a global compliance review from two weeks to under thirty minutes. Before that I engineered portfolio optimization and risk systems at Wilshire for institutions managing more than $1 trillion, and prototyped fraud detection at Microsoft. Today I build LLM and agent systems. If you work in finance and want to use AI well, I can help you pick the problems where it genuinely pays off, build something that holds up when compliance and real money are involved, and tell a real result from noise or overfitting. I also coach people moving into AI-in-finance roles. I've been through the current interview process at quant funds and AI labs myself, so I know what the bar looks like now.
Arthur can help with:
AI Automation
AI Financial Modeling
AI Fundamentals
Automated Financial Reporting
Financial Forecasting
Fraud Detection & Prevention
Investment Research
Risk Assessment
Work Experience

Lead AI Engineer
Stealth Startup
November 2023 - Present
• Architect novel hybrid AGI frameworks integrating generative models, fuzzy logic, and graph-based reasoning for next-generation cognitive architectures. • Design scalable ML pipelines leveraging PyTorch and transformer-based models for real-time knowledge graph augmentation and diffusion modeling. • Lead end-to-end research-to-deployment cycle across distributed systems, including model optimization for performance and energy efficiency on GPU clusters.

Risk Management Machine Learning Quant
Western Asset Management
April 2018 - October 2023
• Designed and deployed machine learning models to predict risk weights of fixed-income securities, achieving >99% out-of-sample accuracy. • Developed NLP-driven compliance automation tools reducing global regulatory review time from 2 weeks to under 30 minutes. • Built predictive cash flow forecasting models integrating market, client, and transaction data streams — improving operational efficiency by 40%. • Collaborated with senior portfolio managers and IT to productionize models across internal analytics infrastructure.

Senior Manager|Senior Specialist
Publicis Sapient
July 2017 - March 2018
• Led cross-functional ML teams developing deep learning NLP platforms for automated email classification used by Fortune 500 clients. • Designed and implemented product recommendation engines for asset management clients, delivering deployment-ready solutions across cloud and on-premises systems. • Advised executive stakeholders on AI strategy, data governance, and infrastructure modernization.

Data Solution Architect
Microsoft
December 2015 - May 2017
• Developed and presented end-to-end big data and ML solutions using Azure ML, Cognitive Services, and Cortana Intelligence Suite to enterprise clients. • Created fraud detection and recommendation system prototypes processing hundreds of millions of transactions annually with significant uplift in accuracy and ROI. • Spearheaded BI and real-time data visualization systems for national mortgage and transportation clients using Power BI, Azure Data Factory, and SQL pipelines.
Sr Data Analyst
OpenX Technologies
December 2014 - June 2015
• Analyzed 100+ billion monthly RTB transactions to optimize advertiser and publisher outcomes using R, Python, and Hive. • Developed statistical models to increase ad exchange revenue and buyer efficiency across high-frequency bidding systems.

Senior Quant Software Engineer
Wilshire
December 2005 - September 2014
• Engineered quantitative optimization models in C++ and MATLAB for multi-asset portfolio management systems used by global institutions with AUM > $1T. • Enhanced mean-variance optimization algorithms with custom constraint support and turnover control, boosting performance by 1000% on large-scale equity portfolios. • Designed and optimized Java- and SQL-based multi-asset risk systems, improving computational efficiency by 50% and ensuring accurate performance attribution. • Provided leadership on migrating legacy optimization engines to state-of-the-art numerical solvers, enabling next-generation product capabilities.
Education

University of Pennsylvania
Doctorate , Physics
1997 - 2003
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