David Agyei

About Me

Data Analyst & Software Engineer specializing in ML/AI

David Agyei

I'm a data analyst and software engineer specializing in ML/AI applications, currently studying Computational & Applied Mathematics at the University of Chicago. I build AI-powered tools and data solutions that solve real-world problems through intelligent automation.

My experience spans data engineering internships where I built ETL pipelines and BI platforms, AI agent development using LangGraph and LLMs, and full-stack applications. I've worked with organizations to automate workflows, improve data quality, and deliver actionable insights through dashboards and analytics.

Technical expertise: Python (pandas, NumPy, scikit-learn), SQL, TypeScript/JavaScript, LangGraph agents, FastAPI, AWS, and React. I focus on building reliable, scalable solutions with proper validation, monitoring, and clean architecture.

Technical Skills

AI & Machine Learning

AI Agents: LangGraph workflows, structured extraction, automation

ML Tools: scikit-learn, pandas, NumPy, Matplotlib, statsmodels

LLM Integration: Gemini 2.0, RAG systems, prompt engineering

Data Engineering

ETL Pipelines: data validation, reconciliation, quality checks

Storage: PostgreSQL, Google Sheets API, CSV processing

Analytics: KPI design, BI dashboards, time series analysis

Software Engineering

Languages: Python, SQL, TypeScript, JavaScript

Frameworks: FastAPI, React, Streamlit, AWS serverless

Tools: Git/GitHub, Pydantic validation, automated testing

Financial Analytics

Portfolio Analysis: optimization, risk metrics, performance tracking

Forecasting: Monte Carlo simulation, scenario analysis

Visualization: Plotly, interactive dashboards, reporting

Relevant Coursework

Fall 2023

First Quarter

CMSC 14100 Introduction to Computer Science I
MATH 15100 Calculus I
PHYS 13100 Mechanics
Winter 2024

Second Quarter

PHYS 13200 Electricity & Magnetism
MATH 15200 Calculus II
Spring 2024

Third Quarter

MATH 18300 Mathematical Methods in the Physical Sciences I
Fall 2024

First Quarter

MATH 19620 Linear Algebra
Winter 2025

Second Quarter

MATH 15910 Introduction to Proofs in Analysis
CMSC 14200 Introduction to Computer Science II
Spring 2025

Third Quarter

MATH 20250 Abstract Linear Algebra
CMSC 14300 Introduction to Systems Programming I
CMSC 25300 Mathematical Foundations of Machine Learning
Summer 2025

Fourth Quarter

FINM 25000 Quantitative Portfolio Management and Algorithmic Trading
CMSC 27100 Discrete Mathematics
Autumn 2025

First Quarter

MATH 20300 Analysis in Rn I
MATH 21100 Basic Numerical Analysis
STAT 24400 Statistical Theory and Methods I
Winter 2026

Second Quarter

CMSC 25400 Machine Learning
MATH 20400 Analysis in Rn II
STAT 24500 Statistical Theory and Methods II