Developed Canis, a gradient-boosted forecasting model that ensembles deep neural networks (TCN, Stacked BiLSTM, CNN-LSTM, Transformer) with probabilistic and simulation forecasts, reducing RMSE by 25%. Engineered and analyzed large datasets with time series, spatial data, and historical aggregates, improving model accuracy by 5%. Collaborated with stakeholders to deploy and monitor the model, optimizing path planning, tool utilization, and procurement. Evaluated performance through regression analysis, and presented results to senior leadership.

Data Science Skills:- Converted backend R script to Python responsible for process organization and scoring.- Applied debugging techniques and relevant unit test creation to validate data output.- Completed internal certifications for data querying, munging, and statistical analysis (eg. Kruskal-Wallis vs. ANOVA)Machine Learning:- Developed machine learning models including k-nearest neighbors, regression, and linear classifiers.- Completed Data Camp Courses in Supervised and Unsupervised Learning.- Used advanced techniques like PCA, NMF, and decision trees (XGBoost).- Applied hyperparameter tuning, model analysis, and ensemble methods.- Utilized data munging, feature engineering, and model assessment.Software Engineering:- Contributed to building a Django-ninja API for data loading to SPOTFIRE.- Assisted in rate limiting, caching, and security strategizing.- Documented projects and facilitated fellow interns' work using Jupyter Notebooks.Manufacturing Engineering:- Observed process controls, statistical process controls, and quality event tracking.- Compiled a presentation and communicated an overview of projects completed during the internship.Global Recognition:- Chosen for a prestigious opportunity to travel to Samsung's headquarters in Korea.- Engaged in advanced problem-solving sessions and discussions.- Gained insights into cutting-edge practices and methodologies in the industry.- Deepened understanding of how international relationships influence a top-ranked global brand, especially in relation to overseas subsidiaries.