DATA SCIENCE · MOLECULAR ML · LAB AUTOMATION
Your Name
Data Scientist — ML for Chemistry & Pharma
I build machine learning systems that predict molecular properties and turn raw lab instrument data into production-ready reports — end to end, mostly solo.
LCMS Automation Platform
Turns raw mass-spec instrument files into analysis-ready reports, automatically, for dozens of scientists a day.
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Agentic AI System
An agent-driven pipeline that adapts to unpredictable lab-report layouts instead of relying on one fixed template.
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[Project 3 — add a title]
[One punchy line summarizing the project, 10–15 words.]
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The stack behind the work
ML / AI
- Molecular property prediction (ADMET, permeability)
- AutoML
- Spectral classification (FTIR)
- Cheminformatics
- LLM agents & prompt orchestration
- scikit-learn / XGBoost
Backend
- Python
- CherryPy
- REST API design
- Concurrent & parallel processing
Infra
- AWS EC2
- ThreadPoolExecutor / ProcessPoolExecutor
- PyInstaller packaging
- Deployment & monitoring
Tools
- pandas / NumPy
- rainbow (Waters .raw)
- nmrglue (NMR)
- Tkinter
- Excel / Word report generation
- Git
Machine learning, grounded in the lab.
I'm a data scientist working at the intersection of machine learning and pharmaceutical chemistry — building models that predict molecular properties and systems that automate the lab data pipelines chemists rely on every day.
I started as a data science intern in 2024, working on AutoML for ADMET property prediction, and converted to a full-time role after six months. Since then I've built and shipped most of these projects solo, end to end — from raw instrument files to production systems used by dozens of scientists.
Experience
2024 (PPO conversion) – Present
Data Scientist
[Company Name]
Own ML and lab-automation projects end to end: molecular property prediction, spectral classification, and the LC-MS automation platform.
2024
Data Science Intern
[Company Name]
Built an AutoML pipeline for ADMET property prediction; converted to full-time after six months.
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