Dr. Claire McDaniel

I’m a data scientist with a Ph.D. in Data Science and over two decades of experience across tech, aviation, retail, and social platforms. My expertise blends machine learning, behavioral modeling, and real-world problem solving to generate actionable insight for product and marketing decisions. I’ve worked with companies like Meta, Microsoft, Lockheed Martin, and American Airlines—and I bring deep empathy for small businesses and underserved consumers.

🔧 Technical Skills

• Programming & Tools: Python, SQL, Scikit-learn, Power BI, Tableau
• Machine Learning: Linear Regression, Random Forest, XGBoost, Gradient Boosting, ElasticNet, Ridge, SVR, Multilayer Perceptron (MLP)
• Statistical Analysis: Hypothesis Testing, RCT, t-test, chi-square, ANOVA, DiD, Mann-Whitney, Kruskal-Wallis, Wilcoxon
• Data Modeling: SEM (Semopy), Uplift Modeling, Customer Segmentation
• Data Engineering: Wrangling, feature engineering, pipeline automation

🧠 Behavioral & Consumer Insight

• Behavioral Modeling: Extended TAM, Identity Theory, Trust & Motivation Constructs
• Human-Centered AI: Interpretable ML, explainability, behavior prediction
• Survey Research: Adaptive logic, factor analysis, psychometric validation

📈 Business & Strategy

• Analytics: Funnel optimization, campaign effectiveness, journey analysis
• Decision Support: Go/No-Go threshold modeling, product adoption forecasting
• Collaboration: Translating data for product, marketing, and executive teams

💼 Professional Strengths

• Ph.D. in Data Science
• MBA, PMP-certified, CBAP, and Scrum Master
• Real-world experience with AI adoption and productivity analysis
• Passionate about empowering founders and small businesses with data

AI Efficiency Evaluation: Used ML + causal inference to evaluate how AI tools impacted employee performance at Microsoft.

Anomaly Detection: Developed unsupervised and semi-supervised models to identify outliers and prevent fraud or operational failure in complex datasets.

Technology Adoption Modeling: Created predictive models using TAM + ML to forecast adoption in AR/VR products.

Product Insights for Startups: Helped early-stage founders de-risk product launches through behavioral survey analysis and market validation tools.

GitHub: Predicting-Augmented-Reality-Virtual-Try-On-Adoption-Using-ML

Discover the framework behind smarter product decisions — now in book form.

Want to collaborate, hire, or connect? I'd love to hear from you.

Email: cemcdaniel1960@gmail.com

LinkedIn: clairemcdaniel