William Szamosszegi

I’m the President & Founder of Sazmining - a global Bitcoin Mining-as-a-Service platform that manages hardware on behalf of clients and delivers freshly mined BTC to their own wallets. Our mission is to make mining accessible, sustainable, and aligned with our customers’ success - 100% renewable energy, transparent economics, and client control of their rewards. 

Before this, I built and scaled multiple teams and tech systems in crypto and AI - focusing on systems that reduce operational friction, align incentives, and build real trust in decentralized networks.

My focus today is on infrastructure that reduces operational risk and increases deterministic trust, from mining operations powered by carbon-neutral energy to deterministic market settlement systems for digital asset ecosystems.

I speak and write about the intersection of Bitcoin infrastructure, energy, and scalable market protocols - and work with ecosystem leaders to move high-stakes systems from theory into real world adoption.

Let’s connect if you’re building or integrating mission-critical crypto infrastructure where rigorous, auditable, and operationally deterministic systems matter.

CEO & Founder & Secretary

Data processing that fosters innovation in Blockchain Technology, Artificial Intelligence, CGI Rendering, and Research. Our computing power supports the next generation of technological development — Web 3.0.

WorldQuant

-Engineered and 15+ high-quality alpha models using WorldQuant’s BRAIN platform, leveraging momentum, mean-reversion, and fundamental signals to drive statistically robust performance.
-Achieved model performance benchmarks (Sharpe > 1.5, Robustness score > 1.2) across diverse market regimes by applying rank, z-score, log, normalization, neutralization, delay, decay,  and winsorization
-Optimized signal construction using factor orthogonalization and validation against market, sector, and sub-industry benchmarks, enhancing cross-sectional performance and minimizing overfitting.
-Iteratively refined alphas based on simulation results, improving signal and reducing turnover

Quant Alpha Researcher

Archaide

-Built 10+ AI-driven trading bots using Archaide’s proprietary platform, integrating LLM with quantitative strategies across momentum, mean-reversion, and options arbitrage, achieving average hitrate >70%
-Benchmarked bot performance against risk-adjusted metrics (Sharpe, Sortino, drawdown) and fine-tuned decision logic based on signal decay, turnover, and transaction cost sensitivity

Quantitative Trader

Wall Street Quants

-Designed and implemented a mean-reversion strategy exploiting multi-pair cointegration among equity, using Johansen test and Principal Component Analysis for dimension reduction and portfolio formation
-Constructed a dynamic portfolio of co-integrated spreads with rolling estimation and adaptive hedge ratios; achieved a Sharpe ratio of 0.8 and Information Ratio of 0.7 post slippage and transaction costs

Quant Research Intern

CIAS Insurance

-Applied web-crawling for data aggregation and performed competitive analysis on major KPIs.
-Conducted time series analysis and built predictive SARIMA and LSTM model on hurricane forecasting to implement risk mitigation on electronic vehicles.
-Utilized SQL for enterprise database management, leading to 10% improvement in data accuracy

Data Science Intern

Purdue University - The Graduate School

-Formulated individual-based improvement plans and fostered course discussions to assist 100+
industry professionals in key learning objectives, resulting in 10% average grades increase
-Extending learning beyond curriculum by advancing applications of various statistical tools

Graduate Teaching Assistant

Maybach Tech

-Conducted market research to optimize product selection, leading to 20% increase in profitability
-Complied excel sheet for streamlining information management
-Managed account payable and account receivable between clients and suppliers
-Implemented qualitative research and stayed current on international trade policy, tariffs, forex rate, industry news, and other economic conditions to assist company’s strategic decision making

Finance Manager

Purdue University

-Analyzed 10+ statistical papers relating to random walk and random matrices
-Utilized matlab for experimenting random matrices to scrutinize the constraints of "bad strings"
-Presented poster to communicate key findings in Purdue Undergraduate Research Symposium
-Organized significant results with latex and assisted the professor in publishing a paper

Research Assistant

I'm a Master’s in Economics candidate at Purdue University with a strong foundation in financial economics, statistics, and data science. With an accelerated STEM undergraduate background in Mathematics and Statistics, I apply rigorous quantitative methods to solve real-world problems in markets and risk.

My experience spans data science, financial research, and academic instruction—ranging from building ARIMA models for insurance risk forecasting and conducting Monte Carlo simulations in mathematical research, to guiding graduate students through advanced econometrics.

Recent projects include developing a statistical arbitrage strategy with a Sharpe ratio above 1.5, and contributing to the NFL Big Data Bowl by applying game theory and risk modeling to scouting analytics.

 I’m actively seeking full-time opportunities in quantitative research or quant trading, where I can combine my technical depth, research mindset, and cross-disciplinary problem solving to generate insights and drive alpha.

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William Szamosszegi

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