Python Data Scientist | Data Automation & Applied ML | Pasadena / LA (Remote-Friendly)

I build production-ready data solutions that turn messy business data into clear insights, automated reports, and deployable ML tools. My background combines software engineering discipline with applied data science, focused on real-world outcomes—not notebooks that die on a laptop.

I help teams and businesses:

• 🔹 Clean, transform, and validate messy data (CSV, SQL, APIs)
• 🔹 Automate recurring reports and dashboards using Python
• 🔹 Build and deploy lightweight ML models (forecasting, churn, scoring)
• 🔹 Turn analysis into running applications and APIs

I’m especially strong at bridging the gap between:

“We have data” → “This runs in production and delivers value.”

Primary

• Python (pandas, NumPy, scikit-learn)
• SQL (Postgres, SQLite)
• Data pipelines & automation

Applied ML

• Regression & classification
• Feature engineering
• Model evaluation & deployment

Backend & APIs

• FastAPI
• REST APIs
• Auth & background jobs

Frontend & Visualization

• Streamlit
• Basic React / JavaScript
• Dashboards & reporting

Deployment

• Docker
• Render / Fly.io
• GitHub Actions (automation & scheduled jobs)

• Bloom Institute of Technology

• Freelance experience in:

  • Data analysis
  • Automation
  • Dashboarding
  • Software & API development

I’ve worked with realistic business constraints: incomplete data, unclear requirements, and the need to deliver fast.

• Freelance / contract work:

  • Data automation
  • Reporting pipelines
  • Applied ML proof-of-value projects

• Full-time roles such as:

  • Data Scientist (Applied)
  • Analytics Engineer
  • Data Engineer
  • ML Engineer (Production-focused)

• 📍 Pasadena, CA (open to remote & LA-based work)
• 💼 LinkedIn: (add link)
• 📅 Quick intro call: (Calendly link)

If you need data solutions that actually run, I’d love to talk.