Coding Projects

Stock Analysis & Grading Model App

Stock analysis app using a custom-built S-F grading model built around evaluating growth-based equity assets that would be held within a 6-12 month period. The app uses both daily batched data via Github Actions orchestration stored in S3 & live data for sepecific UI elements. Reasoning behind why I decided on the current architecture can be found on the 'How it Works' page. Metrics/histiorical prices pulled from Yahoo Finance.

PythonStreamlitGitHub ActionsPandasNumPyMatplotlibScikit-learnPlotlySeabornAWS S3Monte CarloMACDVaRRSIMoving AveragesPrice ForecastingPrompt Engineeringyfinance

GitHubApp URL

Delivery Route Optimization App

Built for Brightside non-profit in Minneapolis MN for their PWYC delivery service to automate the route assignment and distribution process. The app uses a multi-step categorization process using a combination of machine learning clustering and the Google Directions API to create balanced, efficient delivery routes based on the team members that are volunteering to drive that day. This link is a test version of the application using dummy data.

PythonStreamlitPandasScikit-learnK-MeansGoogle APIAWS S3

GitHubApp URL

AWS Athena AI Agent

AI agent interface that allows users to query AWS Athena using natural language. The agent uses AWS Bedrock for secure, enterprise-level AI interactions and converts natural language questions into SQL queries (Prompt-based Semantic Parsing), executes them against Athena, and provides results with analytical summarizations.

PythonStreamlitAWS AthenaAWS BedrockSemantic ParsingPrompt EngineeringPandasGoogle APIAWS S3

GitHubApp URL

Private Credit Solutions Mock ETL & Medallion Master Data Architecture

A mock data architecture for private credit lending, demonstrating a domain-oriented data engineering pipeline built with dbt and Apache Airflow. The architecture follows a medallion-style ingestion and transformation framework, progressing from raw source data through structured and curated domain layers to an analytical output layer. Industry-standard MDM principles (mastered into data domains) are applied at the curated layer to produce clean, governed master data entities. DuckDB is used as the local test target with Snowflake as the production environment, with dbt models handling dialect-switching between the two.

PythondbtAirflowDuckDBSnowflakeMaster Data ManagementData ModelingData OrchestrationETL Pipelines

GitHub

Tableau Public Profile

My Tableau public profile.

TableauPythonPandasBI

GitHubApp URL