David Adams Data science · ML systems · infra-curious
MS-DS student · Building an ML & infra lab

Data science & ML systems with real infrastructure behind them.

I’m David Adams — a data science master’s student wiring together statistics, ML, and a custom home lab (QNAP + gaming rig + Cloudflare) to build production-shaped projects instead of class homework.

MS in Data Science (in progress) Python · R · SQL · Docker · Linux Interested in DS, ML eng, and founder paths

About

Where I am now and what I’m building toward.

I’m pursuing a Master’s in Data Science while building my own lab environment to experiment with statistics, ML models, and infrastructure. My bias is toward systems that would actually run somewhere real: versioned code, reproducible experiments, and secure access.

Long term I’m aiming at roles where I can own the loop from data → model → decision: experimentation, modeling, and the infra that glues everything together — as a data scientist, ML engineer, or founder.

MS-DS student Statistics & inference ML & experimentation Home-lab builder

Skills & tools

Depth in the math & modeling, breadth across the stack.

Data & modeling

  • Python (pandas, NumPy, scikit-learn)
  • R for statistical modeling & inference
  • Classic ML: regression, trees, ensembles
  • Experimental design, A/B testing, power

Data systems

  • SQL & relational database design
  • ETL / data prep in Python & SQL
  • JupyterLab, VS Code, Git workflows
  • Dashboards & basic analytics reporting

Infra & automation

  • Linux, Docker, containerized services
  • Cloudflare Tunnels & Pages (Zero Trust)
  • NAS-backed lab: QNAP + PC + networking
  • Home Assistant & automation wiring

Communication

  • Structured write-ups & docs
  • Explaining trade-offs to non-experts
  • Teaching-oriented visualizations

Projects

This is a snapshot of the systems and experiments I’m building. As I ship more, this section will turn into full case studies with code and write-ups.

Personal ML & data lab
Infra · Networking · Automation

Designed and built a home lab centered on a QNAP NAS and a 13700F/RTX 4060 Ti workstation, all accessible through Cloudflare Zero Trust. JupyterLab, VS Code, and Home Assistant are exposed via tunnels instead of open ports, giving me a secure base to run experiments from anywhere.

QNAP Docker Cloudflare JupyterLab VS Code
Statistical study sheets (in progress)
Python · R · Visualization · Education

Building interactive Jupyter notebooks that visualize distributions, hypothesis tests, and inference workflows. The goal is to hard-wire intuition for statistical tooling I’ll use in ML and experimentation, and to package them as reusable learning assets.

Python R Statistics Visualization
Applied DS roadmap (design)
Roadmap · DS/ML · Product thinking

Designing a ladder of projects that move from intern-ready data work (cleaning, EDA, basic models) to production-shaped experiments and early founder projects in domains I care about: music, finance, and operations analytics.

Data science Experimentation Product mindset

Lab & infrastructure

The lab is where I practice being an engineer, not just a notebook user.

Hardware

  • QNAP NASbook with SSD pool for projects & scratch
  • Gaming rig: Intel i7-13700F, RTX 4060 Ti
  • 10 GbE networking and remote-access setup

Environment

  • JupyterLab running on QNAP for DS/ML work
  • VS Code tunnels for remote coding
  • Home Assistant for automating the environment

Security & access

  • Cloudflare Tunnels for all exposed services
  • No raw port forwards; Zero Trust access control
  • Separate domains for Jupyter, HA, and future tools

Contact

Open to talking about data science, ML, experimentation, and building systems.

Email: davidwhittemoreadams@outlook.com
LinkedIn: https://www.linkedin.com/in/davidadams626

If you’re working on data-heavy problems, ML systems, or infra for analytics products and think I could help, I’m interested in internships, collaborations, and early-stage projects.