Shaya Arya

B.S. Computer Science, Washington State University
Pullman, WA, United States
Abstract

This site presents a comprehensive overview of my technical background, professional experience, and software development portfolio. As a Computer Science graduate from Washington State University, I specialize in quantitative finance applications, algorithmic trading systems, and shell scripting. This portfolio demonstrates practical implementation of financial analysis tools, high-performance computing applications, and business intelligence platforms.

Introduction

Computer Science graduate from Washington State University with a specialized focus on quantitative finance and algorithmic trading systems. My experience spans software development, financial analysis, and mathematical modeling, with particular expertise in building robust trading applications and data analysis tools.

Served as a Teaching Assistant in the EE&CS Department while developing professional-grade financial software. My work emphasizes practical implementation of quantitative methods, combining theoretical knowledge with industry best practices in software engineering and system architecture.

Technical Background

My technical expertise encompasses multiple programming languages and frameworks, with deep experience in Python for financial analysis, Rust for high-performance systems, Shell scripting for automation and system administration, and modern web technologies for application development. Hands-on experience with cloud infrastructure, database management, and distributed systems.

Research Interests

Current focus involves developing algorithmic trading systems, financial data analysis tools, and quantitative research applications. Particularly interested in the intersection of machine learning and financial markets, focusing on practical implementations that can be deployed in production environments.

This work combines mathematical rigor with software engineering principles to create reliable, scalable solutions for complex financial problems. Approach emphasizes both theoretical understanding and practical implementation considerations.

Specializations

Primary areas of expertise include quantitative finance, algorithmic trading, and financial software development. Technical implementation focuses on Python, Rust, TypeScript, AWS infrastructure, Linux systems, and version control workflows.

Technical Competencies

Core Programming Languages

  • Python — Advanced proficiency with NumPy, pandas, scikit-learn, TensorFlow, Keras, Matplotlib, and Plotly
  • Rust — High-performance systems programming and financial applications
  • TypeScript/JavaScript — Modern web development, React, Node.js, and full-stack applications
  • Shell Scripting (Bash) — Automation, system administration, CI/CD pipelines, and workflow optimization
  • C++ — System-level programming and performance-critical applications
  • SQL — Database design, optimization, and complex query development
  • R — Statistical analysis and data visualization
  • MATLAB — Mathematical modeling and numerical computation

Financial and Quantitative Analysis

  • Algorithmic Trading — Strategy development, backtesting, and implementation
  • Options Analysis — Greeks calculation, volatility modeling, and risk assessment
  • Portfolio Management — Risk analysis, optimization, and performance measurement
  • Statistical Modeling — Time series analysis, regression, and predictive modeling
  • Financial Data Processing — Real-time data ingestion, cleaning, and analysis
  • Risk Management — VaR calculations, stress testing, and scenario analysis

Technology Stack and Tools

  • Web Development — React, Next.js, HTML5, CSS3, Tailwind CSS, responsive design
  • Backend Systems — Node.js, Express, RESTful APIs, microservices architecture
  • Database Systems — PostgreSQL, MongoDB, MySQL, time-series databases
  • Cloud Platforms — AWS (EC2, S3, Lambda, RDS, Amplify), distributed computing
  • Development Tools — Git, Docker, CI/CD pipelines, automated testing
  • Machine Learning — Supervised/unsupervised learning, feature engineering, model evaluation

Systems and Infrastructure

  • Operating Systems — Linux/Unix system administration, shell scripting, and server management
  • Version Control — Git workflows, collaborative development, and code review processes
  • Deployment — AWS infrastructure, containerization, and automated deployment pipelines
  • Performance Optimization — Code profiling, memory management, and scalability considerations
  • Testing — Unit testing, integration testing, and test-driven development methodologies

Specialized Knowledge Areas

  • Financial Markets — Options trading, market microstructure, and volatility analysis
  • Data Visualization — Interactive dashboards, 3D analytics, and real-time displays
  • Software Architecture — Design patterns, scalable systems, and clean code practices
  • Mathematical Finance — Quantitative models, statistical analysis, and numerical methods
  • Business Intelligence — Data analytics, reporting systems, and predictive modeling

The intersection of these technical competencies enables comprehensive development of financial software solutions, from high-frequency trading systems to business intelligence platforms. This multidisciplinary approach combines mathematical rigor with practical engineering considerations to deliver robust, scalable applications.

GitHub contribution calendarView profile

Software Development Portfolio

Professional Applications

Stateira Labs Business Intelligence Platform
stateiralabs.com
Production Application — React 18, TypeScript, Electron, AI/ML
Business intelligence platform featuring real-time analytics dashboards, automated data ingestion, and predictive analytics. Responsible for full-stack development, UI/UX design, and system architecture.

Open Source Financial Tools

Average True Range (ATR) Levels
github.com/xeij/atr-level
Open Source Repository — Pine Script, ThinkScript, Trading Indicators
Comprehensive ATR Level Indicator creating horizontal support and resistance levels based on Average True Range calculations from fixed reference points. Features customizable ATR multipliers (0.5x-2x), multiple reference point options (Daily Open, Previous Close, Session High/Low), color-coded level visualization, and comprehensive alert system. Includes volatility assessment, level labels, and session-based calculations for both TradingView and ThinkorSwim platforms.
Volume Analysis System
github.com/xeij/volume
Open Source Repository — Pine Script, ThinkScript, Advanced Volume Analysis
Advanced trading indicator for volume analysis with dynamic volume stacking, momentum tracking, and intelligent alerts. Features multiple calculation methods (Basic/Enhanced/Advanced), volume heatmaps, divergence detection, and volume wave analysis. Includes smart alert system for high volume spikes, real-time buy/sell pressure visualization, and multi-timeframe support for both ThinkorSwim and TradingView platforms.
Pulse Pivot Matrix
github.com/xeij/pulse-pivot-matrix
Open Source Repository — Pine Script, ThinkScript, Trading Indicators
Advanced technical indicator combining 5 EMA Ribbon system (8, 13, 21, 48, 200-period EMAs) with dynamic color coding, conviction signals, and bias analysis. Features ribbon folding visuals, conviction arrows for high-probability trades based on 13/48 EMA crossovers, pullback zones for entry opportunities, and comprehensive trend status displays. Includes real-time alert system and support/resistance levels derived from EMA confluence for both ThinkorSwim and TradingView platforms.
File Deduplication Tool
github.com/xeij/file-deduplication
Open Source Repository — Rust, BLAKE3, Cross-Platform CLI
Fast, safe, and cross-platform command-line file deduplication utility written in Rust. Features parallel directory traversal, BLAKE3 hashing, and multiple actions including delete, move, hardlink, and symlink operations. Includes comprehensive safety features like dry-run mode, confirmation prompts, and detailed reporting with progress bars. Supports flexible filtering by file size, extensions, and paths with multi-threaded processing for optimal performance across Windows, macOS, and Linux.
Linux System Monitor
github.com/xeij/linux-system-monitor
Open Source Repository — C, Makefile, Linux, CLI
High-performance C-based CLI tool for real-time monitoring of CPU, memory, and disk usage on Linux systems. Features beautiful text-based visualizations with colored progress bars and detailed system information. Supports CPU usage breakdown (user/system/idle), memory monitoring with buffers/cache details, and disk usage for any specified path. Includes flexible display options, configurable refresh rates, graceful Ctrl+C shutdown, and cross-architecture support (x86_64, ARM64, ARM32, RISC-V). Optimized for minimal overhead (~50KB memory, less than 0.1% CPU usage) with comprehensive build system and system-wide installation support.
Distributed Task Queue
github.com/xeij/distributed_task_queue
Open Source Repository — Rust, Redis, Tokio, Distributed Systems
Lightweight distributed task queue similar to Celery, built in Rust using Redis as the backend. Features async task execution with Tokio, priority queues (Low/Normal/High/Critical), task scheduling with cron-like expressions, automatic retry with exponential backoff, and horizontal worker scaling. Supports real-time task monitoring, result storage, and graceful shutdown. Achieves 1000+ tasks/second per worker with sub-millisecond dispatch latency and ~10MB memory footprint per worker. Includes comprehensive examples for worker setup, task submission, and scheduled tasks.
High-Performance Web Server
github.com/xeij/highperformance-webserver
Open Source Repository — Rust, Tokio, HTTP/2, Web Server
Minimal and powerful web server built in Rust with async I/O, HTTP/2 support, and flexible routing capabilities. Features Tokio-based async runtime for maximum performance, full HTTP/2 and HTTP/1.1 compatibility, JSON API support with built-in serialization, comprehensive error handling, and graceful shutdown with signal management. Achieves 50,000+ requests/second for simple endpoints with sub-millisecond latency, structured logging with tracing support, and zero-cost abstractions for optimal performance. Includes interactive demo endpoints and comprehensive documentation for rapid development.
TellMe Terminal App
github.com/xeij/tellme
Open Source Repository — Rust, SQLite, Historical Education
Terminal application displaying historical content from 21 historical periods, spanning Prehistoric times through Contemporary era. Features intelligent content filtering, AI-powered recommendations, typewriter effects, and auto-update system. Processes Wikipedia articles through sophisticated scoring algorithms to prioritize engaging historical stories over dry encyclopedia entries, creating an immersive educational experience.
Jane Street Puzzle Solutions
github.com/xeij/janestreet-puzzle
Open Source Repository — Python, C++, Mathematical Computing
Solutions to Jane Street's monthly mathematical and algorithmic puzzle challenges. Demonstrates problem-solving skills in competitive programming, algorithm design, and mathematical reasoning through systematic approaches to complex logic puzzles and optimization problems.

These projects demonstrate practical application of software engineering principles to financial analysis and quantitative trading. Each implementation emphasizes code quality, performance optimization, and real-world usability while maintaining high standards for documentation and testing.

Contact Information

Shaya Arya
Computer Science Graduate & Software Engineer
Washington State University, Pullman, WA

Email: shaya13arya@gmail.com
GitHub: github.com/xeij
LinkedIn: linkedin.com/in/xeij
Calendly: calendly call

Current Positions

Washington State University
Teaching Assistant
Academic Position — EE&CS Department
Computer Science graduate with focus on quantitative methods and financial applications. Serving as Teaching Assistant, providing student support, curriculum assistance, and laboratory instruction.
Stateira Labs
Lead Developer & Quantitative Analyst
Professional Position — Financial Technology
Leading development of AI-powered business intelligence platform with focus on quantitative analysis and predictive modeling. Responsible for full-stack development, system architecture, and implementation of advanced analytics features.

Professional Involvement

Academic and professional organizations at Washington State University:

  • Finance, Insurance & Real Estate Club — Active member focusing on quantitative finance applications
  • Game Development Club — Contributing to software development projects and technical discussions
  • Mathematics Club — Participating in mathematical modeling and problem-solving activities
  • Sigma Alpha Epsilon (ΣΑΕ) — Brotherhood member with community service involvement

Research Collaboration

Open to collaboration and discussion on projects related to quantitative finance, algorithmic trading systems, financial data analysis, high-performance computing applications, machine learning in financial markets, and web development architectures.

Professional inquiries regarding software development opportunities, technical discussions, or collaborative projects are welcome. Response time for professional correspondence is typically 1-2 business days.