RÉSUMÉ
Profile
Experienced in predictive modelling and quantitative analysis using statistical methods and programming languages; interested in using data to develop insights for business and product decisions; experienced in data visualization techniques and tools
Skills
Software and Programming
Python Modules
Machine Learning
Statistical Methods
Data Management
Data Visualization
Python · R · Stata · HTML+CSS · Excel · Unix Shell Scripting
Pandas · Numpy · Scikit-learn · Scipy · Statsmodels · Tensorflow · Keras · NLTK · Beautifulsoup · Graphlab
Deep Learning Neural Networks · Bayesian Modeling · Feature Engineering · Dimensionality Reduction · Regression · Regularization · Ensembles · SVM · KNN · Clustering · Optimization · BSTS + ARIMA · Recommendation Engines
Probability · Bayesian Statistics · Time Series · Regression Models · A/B Testing · Hypothesis Testing · Experimental Design
SQL · AWS
Tableau · Matplotlib · Bokeh · Plotly
Coursework
Convolutional Neural Networks by deeplearning.ai on Coursera Structuring Machine Learning Projects by deeplearning.ai on Coursera Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization by deeplearning.ai on Coursera
Neural Networks and Deep Learning by deeplearning.ai on Coursera
Education
General Assembly - Atlanta, GA (Summer 2016)
Data Science Immersive: A 12-week full-time program with over 600 hours of professional training and practices of Data Science applications. Developed skills in machine learning, statistical methods, Python and data visualization techniques through the project-based curriculum.
Vanderbilt University - Nashville, TN (2014 – 2016)
Master of Arts in Economics
Lawrence University - Appleton, WI (2010 – 2014)
Bachelor of Arts, Economics & Chinese (Mandarin)
Study Abroad: Minzu University of China Beijing, China (two semesters)
Work Experience
Associate Data Scientist – 360i Jan. 2017 – July 2017
-
Designed and built a production-ready predictive model and optimization system using Bayesian Structural Time Series and a gradient descent optimization module with the aim of allocating budget and improving efficient metrics (e.g. ROAS, CPR)
-
The above system enables non-analytics employees to access key insights in near real-time and potentially saves 40+ hours a quarter per team depending on the frequency of budget revisions
-
Built applications using statistical concepts and machine learning algorithms for forecasting and performance analysis using Python and R
-
Delivered EDA, ROI and ETL analysis for retail and service clients
-
Analyzed and visualized customer’s exposure path using Bokeh
Instructional Associate – General Assembly Oct. 2016 – Jan. 2017
-
Met consistently with students to chart their progress and provide ongoing support
-
Built a recommendation engine for teaching purposes
-
Conducted ongoing student communication around course progress
-
Assisted lead instructor in lesson planning and creation
-
Provided homework support and grading feedback
Deal Advisory Graduate Intern – KPMG Nigeria Summer 2015
-
Collaborated with fellow interns in conducting research on specific industries in Nigeria and creating reports about these industries for clients
-
Researched and analyzed company and industry reports that will be necessary for the creation of an information memorandum for fund-raising purposes
-
Created data books for clients, which will later be used for due diligence purposes
Languages
English, Fluent; Yoruba, Native; Chinese (Mandarin), Proficient; French, Basic; Spanish, Basic
Awards
Deans’ List (2012 – 2014); Mellon Senior Experience Grant Recipient (2013); Patricia Ritter Prize in Chinese Culture (2014); Vanderbilt University Hult Prize Winner (2015); Vanderbilt University GPED Award (2016)