TeamBlueLock
A financial operations platform for small businesses. The app brings inventory, ingredient costing, recipe management, and profit analysis into one dashboard.
Next.js • MongoDB • Playwright • JestAvailable for finance, data, and technology opportunities
Daniel Nnodim
Computer Science × Economics
I build at the intersection of finance, software, and research. My work combines full-stack development, financial analysis, data-driven thinking, and a practical interest in how technology can make better decisions easier.
Selected Work
Projects I have built and explored.
AI Stock Prediction Research
A research project where I tested machine-learning models on financial indicators and market data to understand how difficult short-term stock prediction can be in practice.
Python • Finance • Machine LearningPersonal Finance Tracker
A budgeting and financial management app with transaction tracking, spending categories, balance summaries, savings goals, and a demo dashboard for quick review.
Flask • SQLite • Python • FinanceRoommate Matching Platform
A student housing concept focused on roommate discovery, profiles, messaging, and matching across schools.
React • Full Stack • Product DesignAll-in-One Utility App
A multi-tool web app that brings everyday utilities into one place, including weather, calculations, currency conversion, QR scanning, notes, and a playable game.
Next.js • React • Utility ToolsFinancial Data Research Toolkit
A quantitative workflow using regression models, robust standard errors, multicollinearity checks, and financial datasets to support empirical analysis.
R • Econometrics • Quantitative FinanceResearch
Research Question
Does R&D investment intensity predict annual stock returns differently across technology and non-technology firms?
Analysing the Impact of R&D on Stock Returns
Empirical finance study testing whether R&D investment intensity predicts annual stock returns for 100 publicly traded firms, split between technology and non-technology sectors.
Model Logic
Short research design from inputs to interpretation.
01
Inputs
R&D intensity, firm size, profitability, and sector classification.
02
OLS Regression
Tested whether R&D investment predicts annual stock returns.
03
Finding
R² ≈ 0.01
No statistically significant R&D premium detected.
04
Interpretation
Consistent with Efficient Market Hypothesis reasoning.
Network Technician
Luther College ITS — 2025
DevOps Engineer Intern
NNPC Limited — 2024
Resident Assistant
Luther College Residence Life — 2023–2026
Experience
Operational, technical, and financial exposure.
My experience spans enterprise infrastructure, DevOps automation, finance leadership, residence life budget management, and administrative operations.
About
Built across continents. Focused on finance.
My background spans three countries and two disciplines. That combination shaped how I approach problems: analytically, quantitatively, and with a global perspective.
01
Nigeria
Early exposure to business, markets, and entrepreneurship.
→
02
India
UWC Mahindra College and an international academic foundation.
→
03
United States
Computer Science + Economics at Luther College.
Finance
Research
Software
Leadership
Contact
Let’s connect.
Open to roles and conversations across finance, data analytics, investment analysis, and software-backed financial operations.