Nadine Shill
Generative AI, Data Analysis, and Mathematics
3+Years Exp
40+Hours/Week
60%AI
40%Data Analysis
Education & Experience
Johns Hopkins University
Master of Science in Applied & Computational Mathematics (Nov. 2022 – Current)
University of Colorado Denver
Bachelor of Arts in Psychology (Aug. 2015 – Dec. 2021)
Solari
AI/ML Engineering Intern (Feb. 2025 – Current)
Johns Hopkins University
Statistics & Probability Learning Assistant (Jan. 2025 – Current)
Scale AI
Mathematics Senior Reviewer/Queue Manager (Jan. 2023 – Current)
University of Minnesota
Quantum Computing Researcher (Jan. 2024 – Mar. 2024)
Projects
- Anomaly Detection Fraud on XGBoost: Model trained and deployed to detect credit card fraud.
- Unsupervised Learning Clustering using Kmeans: Clustering model trained on housing data.
- LSTM Project (RNN): Predicting text based on prior sequences.
- Best Route for Wildfire Navigation Model: Calculated shortest routes using public APIs.
Certifications
- Machine Learning/AI Engineer Path (Codecademy)
- Deep Learning Specialization (deeplearning.ai)
- Machine Learning Specialization (deeplearning.ai)
Skills
- Python (Django, FastAPI), SQL (MySQL, PostgreSQL), NoSQL (MongoDB)
- ML architectures (MLFlow, TensorFlow, PyTorch, LLMs, Deep Neural Networks)
- Data Analysis, Data Visualization (Tableau, Pandas, Statistical Testing)
- Application Deployment on Streamlit, AWS, Azure; Git, Confluence