Applied Data Scientist | Machine Learning Engineer (Entry-Level)
I build end-to-end machine learning systems using Python, focusing on models that solve real-world problems and balance performance with practical constraints.
My work spans fraud detection, recommender systems, computer vision, and NLP, with an emphasis on evaluation, interpretability, and business impact.
End-to-end imbalanced classification project using Logistic Regression and XGBoost, with a focus on precision/recall trade-offs, ROC-AUC, and threshold tuning for real-world decision making.
➡️ Applied ML, evaluation, business interpretation
Personalized recommender system using collaborative filtering and content-based methods, evaluated with RMSE and Top-N recommendations.
➡️ Recommender systems, similarity search, embeddings
Multi-class image classifier built with TensorFlow/Keras, applying convolutional architectures and regularization to reduce overfitting.
➡️ Deep learning, unstructured data
Text classification pipeline using TF-IDF, feature engineering, and logistic regression to detect spam messages.
➡️ NLP preprocessing, classical ML
Languages: Python, SQL
Machine Learning: Scikit-Learn, XGBoost, feature engineering, model evaluation
Deep Learning: TensorFlow (CNNs, MLPs), embeddings
NLP: Text cleaning, tokenization, TF-IDF, classification
Data & Tools: Pandas, NumPy, Matplotlib, Jupyter, VS Code, Git/GitHub
Cloud: AWS fundamentals (S3, EC2, Lambda, SageMaker basics)
- Machine Learning Specialization — DeepLearning.AI / Stanford Online (Andrew Ng)
Supervised ML, Advanced Algorithms, Unsupervised Learning, Recommenders - Automation and Scripting with Python — Microsoft (Coursera)
- Data Analysis and Visualization with Python — Microsoft (Coursera)
- Python Programming Fundamentals — Microsoft (Coursera)
- Introduction to Software Engineering — IBM (Coursera)
- Currently pursuing: AWS Certified Machine Learning Engineer – Associate (MLA-C01)
- AWS SageMaker training and deployment pipelines
- Model optimization (GridSearch, RandomSearch, Optuna)
- ML system design and real-time inference
- Feature stores, monitoring, and model drift detection
I’m actively seeking Applied Data Scientist I or Machine Learning Engineer I opportunities.
Open to collaboration, mentorship, and building production-minded ML systems.
🔗 LinkedIn: https://www.linkedin.com/in/juante-wilson-044771280/
🔗 Portfolio: https://github.com/Juantew