I decode how algorithms allocate risk, liquidity, and attention across markets. From Navy combat documentation (2004-2009) to Wall Street private equity (2015-2020) to founding my boutique research practice (2020-present), I map how technical systems encode incentives and concentrate advantages. I build decision systems for systematic funds and publish research on market microstructure and algorithmic accountability.
After military service, I completed degrees at Full Sail University (2009-2011) and taught digital journalism there through 2014. My transition to finance came through Patriarch Partners on Wall Street, where I led digital transformation across 11 portfolio companies. Since 2020, I operate an independent practice serving hedge funds and systematic managers in equities and macro strategies.
From Battlefield Documentation to Algorithmic Investigation
Combat Camera Specialist: Learning to See What Others Miss
As a Mass Communications Specialist from 2004 to 2009, I documented both combat and humanitarian operations across multiple deployments. Managing 20,000+ photographs and hours of HD video taught me that every image tells a story, but the most important stories are often hidden in the metadata. I built resilient 12-terabyte media infrastructures under extreme conditions, developing systems that could preserve truth even in chaos.
This experience taught me three critical skills I use daily in AI investigation: how to spot patterns in overwhelming data streams, how to build systems that capture what really matters, and how to tell stories that make complex realities understandable. When you’ve documented life-and-death operations, you learn that technical accuracy and human impact are inseparable. This principle now guides my work auditing AI systems that make decisions about loans, jobs, healthcare, and criminal justice.
Wall Street Private Equity: Understanding Systems at Scale
My transition to Patriarch Partners on Wall Street from 2015 to 2020 revealed how algorithms invisibly shape financial outcomes. Leading digital transformation across 11 portfolio companies, I discovered that inefficient systems often worked exactly as designed, just not for the people using them. I reduced non-revenue tech OpEx by 78% at Dana Fragrances (FY2017-FY2019) through ERP consolidation and process automation, while growing portfolio-wide revenue 30% through data-driven pricing optimization.
This wasn’t just about efficiency metrics. I learned to reverse-engineer the hidden logic in enterprise systems, uncovering how technical architecture creates competitive advantages. Managing Shopify migrations, Microsoft Dynamics implementations, and 3PL integrations showed me how subtle design choices compound into market power. This experience became the foundation for my current research on algorithmic market structure.
Independent Quantitative Researcher: Building Systems That Work
Since 2020, I operate a boutique research practice serving hedge funds and systematic managers in equities and macro strategies. My Z-Score Probability Indicator achieved a 20% lift in directional hit rate over RSI baselines on daily bars for S&P 500 constituents (2014-2024, walk-forward cross-validation, no survivorship bias). The agentic research system I developed using Polygon and FRED APIs reduced client research cycle time by 62% (Q1 2024 client benchmark).
Every model I build serves dual purposes: solving immediate client problems while advancing research on market microstructure. This is not conjecture; it’s pattern analysis on labeled market events, reconciled against execution data and public microstructure research. My work focuses on empirically observable feedback loops between sentiment signals and order flow dynamics.
By the Numbers
Q1 2024 hedge fund benchmark
21s avg watch, education vertical
S&P 500, 2014-2024 backtest
Dana Fragrances FY17-19
Digital transformation
Full Sail University
“Every algorithm encodes the values, biases, and incentives of its creators. My mission is to decode these hidden values, expose who benefits from them, and reveal alternative possibilities.”
Technical Arsenal
My toolkit combines cutting-edge AI development with investigative methodologies. I don’t just build models; I interrogate them, stress-test them, and expose their hidden assumptions. Every tool serves a purpose in revealing how algorithms shape our world.
Core ML Stack
Quantitative Finance Tools
AI Governance Frameworks
Current Investigations
My work focuses on three critical areas where algorithms increasingly determine human outcomes: financial markets, social systems, and emerging technologies. Each investigation reveals how code becomes power, and how that power shapes society in ways we’re only beginning to understand.
Market Microstructure Pattern Research
My current research documents sub-second correlations between large sentiment shifts and order book dynamics consistent with algorithmic responses. Using transaction-level data from major exchanges, I analyze feedback loops between social signals and execution patterns that affect price discovery. This work aligns with SEC market structure proposals on tick sizes and payment for order flow reforms.
Real-Time Economic Dashboard
I built a serverless economic forecasting system that runs entirely on Cloudflare Workers, processing macro data from FRED and market data from Polygon every 15 minutes. The dashboard calculates composite scores across growth, stability, momentum, and sentiment factors, then generates probability distributions for market outcomes across multiple time horizons. It includes a custom volatility estimation model that maintains accuracy even when official VIX data is unavailable. The system demonstrates how edge computing can deliver institutional-grade market intelligence without traditional infrastructure costs.
The Gray Files Podcast
Every week on The Gray Files podcast, I investigate a different algorithmic system shaping our world. From facial recognition in public housing to algorithmic wage theft in gig economy apps, I break down complex technical systems into understandable stories about power and justice. Recent episodes have exposed how credit scoring algorithms encode racial bias, how social media algorithms radicalize users for engagement, and how healthcare algorithms deny coverage to maximize profits.
Miami’s Tech Revolution
Based in Wynwood, I’m embedded in Miami’s explosive fintech and crypto scene, investigating how the city’s regulatory experiments enable both innovation and potential harm. My work examines Miami’s embrace of blockchain technology, its experiments with city coins, and the influx of tech companies reshaping local economics. I’m particularly focused on how Miami’s position as a gateway between North and South American markets creates unique opportunities for algorithmic arbitrage and potential manipulation.
The Future of Algorithmic Investigation
As we enter the age of artificial general intelligence, large language models making critical decisions, and quantum computing breaking current encryption, the need for algorithmic investigation has never been greater. My work is evolving to meet these challenges.
I’m currently researching how quantum optimization will affect portfolio construction and execution strategies. Banks and exchanges are running pilots in quantum annealing for route selection and collateral optimization. My investigation tracks these developments while building models to detect potential quantum advantages in market data before they destabilize traditional strategies. This monitoring includes analysis of D-Wave partnerships with financial institutions and IBM’s quantum network experiments.
Large language models are becoming the primary interface between humans and information. My current research investigates how these models encode biases, who controls their training data, and how their responses shape public opinion. I’m developing tools to audit LLM outputs for systematic biases and investigating the concentration of power among the few companies controlling these models.
Through coalitions with researchers, activists, and policymakers worldwide, I’m working to create standards for algorithmic accountability. This includes contributing to EU AI Act implementation, advising on NIST frameworks, and developing open-source tools for algorithmic auditing. The goal isn’t just investigation but systemic change: creating a world where algorithms must be transparent, accountable, and aligned with human values.
Ready to Decode the Algorithm?
Whether you’re fighting algorithmic bias, building ethical AI systems, investigating digital power structures, or simply trying to understand how algorithms shape your world, I’m here to help expose the truth and build better alternatives.