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Top Skills

  • Machine Learning
  • Time-Series Analysis
  • Data Science
  • Python
  • Cloud Computing
  • Full-Stack Development

Summary

Results-driven AI/ML Engineer, Data Scientist, and Software Engineer with expertise in developing scalable machine learning models, cloud-based ML systems, and full-stack applications. I specialize in predictive analytics, real-time inference, and automation solutions, optimizing workflows and enhancing decision-making across multiple industries, including finance, healthcare, and material science. I have a proven track record of securing government contracts, leading R&D efforts, and deploying high-performance AI solutions. I'm passionate about bridging the gap between cutting-edge research and practical AI deployment to drive business impact.

Experience

Freelance Software Engineer and Consultant - Self-Employed / NextFrame Analytics (October 2024 - Present)

  • Developed and deployed AI/ML-powered applications for research and financial sectors, enhancing predictive accuracy by 15% and optimizing millions of financial strategies.
  • Built scalable ML pipelines, enabling 100 TPS real-time inference, automated model retraining, and cloud deployment.
  • Designed and implemented an algorithmic trading optimization system leveraging reinforcement learning, improving financial modeling performance.

Research Engineer - AIMdyn, Inc. (October 2022 - November 2024)

  • Developed ML inference systems and APIs for high-impact government projects, improving decision-making capabilities.
  • Led R&D efforts for DARPA, securing a $1 million contract in AI-driven predictive modeling.
  • Achieved 10% relative RMSE for multi-state, 100-step ahead predictions.
  • Designed and implemented advanced algorithms using Koopman operator theory, enhancing dynamic environment simulations.
  • Developed and deployed efficient ML pipelines for processing large datasets, improving data analysis speed and accuracy.

Data Scientist - Brooksource (Contractor for Deloitte US - Data and Analytics) (June 2022 - October 2022)

  • Developed AI-driven anonymization frameworks, reducing data breach risks by 40% for enterprise clients.
  • Optimized data engineering pipelines, improving efficiency and scalability by 35%.
  • Created generative AI models in Python for data anonymization, enhancing data handling processes.

Graduate Researcher - Cal Poly, San Luis Obispo (September 2021 - June 2022)

  • Developed a COVID-19 forecasting model, improving predictions by 15% compared to ARIMA models.
  • Presented research on network-based ML methods for public health applications, influencing policy recommendations.

Research Intern - University of California, Los Angeles (May 2019 - September 2019)

  • Built an AI-based deforestation prediction model with 86% accuracy using time-series satellite data.
  • Enhanced spatial ML analysis, increasing prediction accuracy by 20% through advanced feature engineering, including principal component analysis (PCA), texture analysis, multi-spectral feature extraction, and synthetic feature augmentation for spatial-temporal modeling.

Projects

StrategyQuant Clone

  • Optimized and backtested 100,000+ trading strategies using backtrader, pandas, numpy, and yfinance.
  • GitHub Repository

ERCOT Scraping Module

  • Scraped over 1TB of market data from the ERCOT API, optimizing SQL queries for large-scale data extraction and improving database efficiency.
  • GitHub Repository

Predictive Maintenance System

  • Backend API supported 1000+ simultaneous users and achieved 84% accuracy in a multi-class problem.
  • GitHub Repository

Technical Skills

  • Machine Learning: Predictive Modeling, Time-Series Analysis, GNNs, Generative AI, Bayesian Optimization, Model Deployment, Transformers for NLP and CV
  • Software Engineering: Full-Stack Development, RESTful APIs, Microservices, Event-Driven Architecture, CI/CD, TDD
  • Cloud Platforms & DevOps: AWS, Azure, GCP, Docker, Kubernetes, Git, Terraform, GitHub Actions, MLflow
  • Programming Languages & Frameworks: Python, JavaScript, SQL, Flask, FastAPI, React.JS, Node.JS, pandas, numpy, scikit-learn, TensorFlow, PyTorch
  • Project Management: Agile, Scrum, Stakeholder Communication, Technical Leadership, Team Mentorship, Cross-Functional Collaboration

Publications & Technical Writing

Education

  • Master of Science in Mathematics with Distinction - Cal Poly, San Luis Obispo (2022)
    Cumulative GPA: 3.8/4.0
  • Bachelor of Arts in Mathematics and Physics with Distinction - Sonoma State University (2020)
    Major GPA: 3.8/4.0, Cumulative GPA: 3.65/4.0
  • Associate of Arts in Computer Science - Allan Hancock College (2017)

Awards & Honors

  • Graduation with Distinction - Cal Poly Department of Mathematics (Spring 2022)
  • Dean's List - Cal Poly School of Science and Mathematics (Spring 2020-Spring 2022)
  • Graduation with Distinction - Sonoma State University (Spring 2020)
  • Green Family's Poster Award - Sonoma State School of Science and Mathematics (Spring 2019)
  • Top Undergraduate Presenter - Fourth Annual Central Valley Region SIAM Student Chapter Conference (Spring 2019)
  • Dean's List - Sonoma State School of Mathematics and Science (Spring 2017-Spring 2020)

Presentations

  • Thesis Defense: A Network Analysis of COVID-19 in the United States - Cal Poly Department of Mathematics (Spring 2022)
  • Senior Thesis: Blackhole Spacetimes - Sonoma State Department of Physics (Spring 2020)
  • Stop-and-Go Oscillations in Dynamic Traffic Networks - Joint Mathematical Congress (Poster) (Spring 2019-Winter 2020)
  • Various Mathematics Presentations - Northern California Undergraduate Mathematics Conference, Central Valley Region SIAM Student Chapter Conference, School of Science & Technology Research Symposium (2019)