Associate Data Scientist

• May 2021 - Present

Utilizing analytics and machine learning to solve business problems in warehouse operations, supply chain planning, and customer service. Tech Stack: SQL, Snowflake, Python, Git, Github, Github Actions Utilizing analytics and machine learning to solve business problems in warehouse operations, supply chain planning, and customer service. Tech Stack: SQL, Snowflake, Python, Git, Github, Github Actions

Data Analyst

• Jul 2020 - Sep 2020

Collaborating with team to explore disparities in guest service utilization and exit outcomes to better target guest services. Collaborating with team to explore disparities in guest service utilization and exit outcomes to better target guest services.

Data Science Fellow

• Mar 2020 - Jun 2020

A 13-week hands-on immersive training program in all aspects of the data science pipeline utilizing Python and open-source packages. - Data Collection: Web Scraping, API Requests, SQL Queries, and File Imports - Data Cleaning: Text NLP, Missing-values Imputation, Data Quality Validation - Exploratory Analysis: Statistical Tests, Correlations, Summaries - Visualization with Matplotlib, Seaborn, Plotly, & more - Feature Engineering: Interaction, Binning, Transformation, NLP - Modeling: Supervised and Unsupervised ML Algorithms - Optimization: Grid Search, Ensemble Methods, Model Validation Machine Learning Algorithms: - Regression: Ordinary Least Squares, Ridge/LASSO Regularization, Principal Components, Decision Trees, Random Forests, Boosting, XGBoost - Classification: Nearest Neighbors, Logistic Regression, Support Vectors, Trees, Boosting - Forecasting: FB Prophet, ARIMA & SARIMAX, Poisson Regression - Clustering: k-means, DBSCAN - Neural Networks: Convolutional NN, Recurrent NN, LSTM Projects: Subreddit classification utilizing NLP of posts and comments to correctly predict future posts' subreddit utilizing logistic regression, naive-bayes, and a support vector classifier to achieve peak accuracy of 98% compared to only 90% with titles only. Regression estimate of housing sale prices with AMES dataset. Created a Voting Regressor weighing OLS, Random Forests, and XGBoost minimizing Kaggle test RMSE at $18,320, a 60% improvement from baseline and 20% improvement from best OLS model. Map and quantify overlaying natural disaster risks using Python's geopandas and ARCGIS using data collected from various sources on risks such as wildfire, drought, hurricane, drought and COVID-19. Build interactive visualization of flight route networks and airline performance utilizing Bureau of Transportation data sources. Show less

Team Lead

• Jun 2018 - Mar 2020

Sunday production manager leading staff of 10 fulfilling 600-700 orders across 2 departments. Weekday lead guiding for 20-30 production staff in outbound operations within 150+ warehouse staff fulfilling $1-$1.5 million in daily sales. Responsibilities: - Lead onboarding and training of new staff to deliver efficiency targets within 6 weeks - Implement regular audits and continual training to outperform 0.05% accuracy target - Balance labor-demand across functions to meet daily deadlines. - SME in all warehouse operations including outbound shipping, and inventory control procedures - SME in WMS systems utilization, equipment operation, and product knowledge - Identify continuous improvement in process flows, product layout, and safety guidelines Continuous Improvement Successes: - Optimized trailer dock layout in new building to reduce forklift loaders travel by 5% - Automated research for repacking returns process via new WMS inventory system and SQL Show less

Fulfillment Associate

• Jul 2016 - Apr 2018