Bridging data, science & strategy 🚀 Machine Learning 🛠️ Tool Development 📦 R Software 🧭 Leadership 🧬 Life Sciences Domain Expert ✨ Director of Data Science @ Cercle.ai
🔬 Domain expertise: IVF clinical analysis, proteomics, biomarker discovery, predictive modeling
📊 Technical tools: R, machine learning, statistics, experimental design, reproducible research
💪 Strengths: Translating complexity, cross-functional collaboration, storytelling with data
"Making predictions is easy ... making accurate ones is much more difficult." ⎯ Me⎯
I love to solve problems.
Often the problem can be understanding a complex biological process, but it can also be as simple as fixing something that's broken (e.g. a door that jams, a bicycle, or even machine learning software). In particular, I like to apply my data science skills to better understand, or even solve, the problems we face.
I am always open to discuss possible roles 🔭 and whether my skill set can solve problems in your space!
| Machine Learning 🚀 | Statistics 📊 | Open-Source 💻 | Software Tools 🔧 |
|---|---|---|---|
| Random forest | Regression problems | R | Linux🐧, MacOS 🍎 |
| Naive Bayes | Real-world data (RWD) | C++ | Git, GitHub  |
| Lasso regularization | GLMs | CI/CD | AWS |
| k-Nearest neighbour | Causal inference IPTW | LaTeX | BASH, GNU |
| PCA | Survival analysis | Python 🐍 | Docker 🐋 |
| Maximum-likelihood | Linear mixed-effects | Opencode | LLM/Agentic workflows |
- Execute organization's data science strategy, aligning analytics with business and clinical goals
- Instituted a culture of rigorous, reproducible analysis -- shifting the team from reactive one-off requests to disciplined workflows emphasizing data quality as the primary standard
- Deliver causal inference analyses on large-scale reproductive health data (IPTW, propensity scoring, covariate balancing) to inform clinical treatment protocol decisions
- Lead our key pharmaceutical partnerships, translating multi-arm observational results into clinical insights
- Collaborate with customers and C-suite to create framework for data-based decision making
- Architect and maintain a company-wide \R analytics ecosystem -- standardizing workflows from data ingestion through Quarto-driven client reporting
- Build and mentor a data science team of 3-5; own hiring, statistical analysis plans, code review, and technical growth
 False Discovery |
 Mixture Models |
 Logistic Regression |
 Naive Bayes |
 The Birthday Paradox |
 Mack-Wolfe Tests |
 Mixed Effects |
 Monty Hall Paradox |
 Decision Boundaries |
 Class Imbalance |
 Pitch Classifier |
 IPTW |
- 💬 Favorite food: 🐟 🌮
- 📚 I am currently learning woodworking 🪵 ... I'm mostly good at making a lot of sawdust!
- 💬 Ask me about: bikes and
R... I'll talk your 👂 off! - 🚴 I'm an avid cyclist:
come say hi on
