Engineering Lean Six

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raedjamw@WORK EXPERIENCE gmail.com linkedin.com/in/rae-wallace-Rae 65124764/ Wallace 5837 Beacon St, Pittsburgh, PA, 15217 757-***-**** Propel ‘Chameleon harmful IT, Data Data trucking an Trucking Science: Engineering: iNetworks companies Project’ Auto/across Value - - - - Logistics Automated Geocoding Unsupervised Created the Proposition: US geographic Startup- location Web Machine Helps scraping Data data visualizations Insurance Learning Scientist via of ESRI transportation companies using ArcGIS (of January connections the APIs KNN data 2020-make in Algorithm Google online using more Present) Geopandas, via Colab. informed to selenium engineer decisions basemaps, and features. saved by detecting seabron. to MySQL.

Software Engineering: - - - - Generated Unsupervised Project Lean software Tracking new Machine practices features using Github Learning to using classify for pickle using Version new files Hierarchical features to Control make more efficient Clustering optimally. machine Analysis learning to generate models labels. Unequal Technologies, an iNetworks - Streamlined Sportsgear code design Startup using - Strategy defined Lead modules (January 2020-Present) PPG Powergen Industries Boosted ESPN Developed Projected Developed Organized (Trinidad through Automotive sales a data MySQL a $roadmap 45- and by free into $6% 67 Tobago) tables marketing spreadsheets for million Division for the that global – month and Process segmented from – Global expansion $and 50 professional of million March delivered Improvement Market the via by paint markets. strategic orchestrating MLS Research final market soccer presentation Engineering targeting for Intern players National the North distribution (to May Intern by upper brand leveraging Vehicles 2019-(management Jun exposure channels. Sept 2013 and social 2019) Marine – for Aug media. of the the 2013) Markets Halo™ marketing headband respectfully. team. on Personal Lead managers. Projects my team of diverse team members to design and present an improved evacuation plan of the powerplant to plant Iowa Real Estate House Price prediction using advanced Regression Techniques

MSE Machine score Learning 0.0124, Outlier Top 15 Detection % on Kaggle(using first - PCA, attempt)KNN, . DBScan.

Machine Learning Models for Analysis – Tuned gridsearch of Lasso, Ridge, RFE Regression, and XGBoost. Time Series Sentiment Analysis to Predict Real Vs Fake News: Deep Learning and Various Classification Algorithm Education Carnegie MS: Engineering Preprocessed Achieved Achieved Mellon Technology University classification accuracy Reddit between Innovation (data Graduated: accuracy from 80- scratch, Management of 91% May around using: 2019) Implemented 91% Random using TF-Forest, LSTM IDF RNN Naïve and Bag Deep Bayes, of Learning Words Adaboost, for vectorizing and XGboost text classifiers data. MS: Virginia BS: Statistics Mechanical GPA: Tech 3.(44 Graduated: Engineering August 2017) BS: Relevant Systems Coursework Engineering

Skills Strategy Bayesian Data Mining and Machine in Management R Learning of in Tech Python Innovations

Python, Intermediate MySQL, French R, Microsoft Office, Google Colab, Git/Github Version Statistical Engineering Numerical Control, Computing Methods Tensorflow, Project Management Sklearn, Apache PySpark

Lean Six Sigma Green Belt