Data Machine

Emi Harry

New York, ***** • +1-415-***-****

***.*****@*****.*** • http://linkedin.com/in/EmiHarry

Education

Deep Learning Specialization (Coursera); DeepLearning.ai December 2018

Applied Data Science with Python Specialization (Coursera); University of Michigan Ann Arbor, MI. December 2018

Master of Science in Data Analytics; Fordham University New York, NY May 2018

GPA: 3.53

Machine Learning Certificate (Coursera); Stanford University Stanford, CA November 2017

Data Science Specialization (Coursera); John Hopkins University Baltimore, MD June 2017

Business Analytics Specialization (Coursera); University of Pennsylvania, Wharton Philadelphia, PA August 2016

Master of Social Entrepreneurship; Hult International Business School San Francisco, CA August 2015

Bachelor of Science in Mathematics; University of Lagos Lagos, Nigeria December 2009

Member: National Society of Black Engineers, Mathematics Association of America, Project Management Institute, Society of Women Engineers

Skills

Machine Learning, Data Cleaning and Manipulation, Data Analysis, Development of Data Products, Research, Presenting

Technologies: R, Tableau, Hadoop/MapReduce, Microsoft (Excel, Azure ML Studio, Power BI), SQL, Python, SPSS, SAS, AWS, ReactNative, Android Studio, Firebase

Experience

Tutor, Computer & Information Science Dept., Fordham University¬ New York NY February 2018 – May 2018

• Helped students solve problems with their python programming for data science, computer theory, and mathematics assignments.

Data Scientist Intern, NBCUniversal New York, NY September 2017 - December 2017

• Cleaned and manipulated over 12GB of messy customer data with R by utilizing grep function and sqldf package to place in structure for seamless analysis.

• Analysed the data in R using quantitative comparative analysis to harness factors that could readily highlight the watching habits of consumers across the various television brands, and generated visualizations and a storyboard report of consumers’ behavioural patterns in Tableau.

Data Scientist Intern, Fordham University IT New York, NY December 2016 - May 2017

• Completed comparative analysis of school’s statistics against competitors in various categories to identify necessary areas of improvement; researched to determine why competitors did better in specific areas.

• Created visualization reports and dashboards using Microsoft Power BI, of the results from the analysis, and developed predictive model to determine number of students who will enroll in the next academic year using supervised machine learning (generalized linear model) in Microsoft Azure ML Studio.

Volunteer Data Scientist, UNICEF Innovation Fund New York, NY October 2016 - December 2016

• Created predictive model to determine which twitter users live in the Favelas (slums) of Rio de Janeiro; researched Rio to gain domain knowledge and geolocation range for the region.

• Parsed over 20GB of Twitter data in R, then utilized the visualization tools in R to identify outliers in the geocodes, which were indicative of virtual private network software usage. After which an initial data pre-processing was done with the hypothesis that twitter users residing in Favelas would not have more than 3000 followers.

• Used unsupervised machine learning, specifically the KMEANS algorithm in combination with geo-digit elimination (to create a grid-based feature assessment), to create the binary class variable of “urban area” and “favela”.

• Implemented supervised machine learning algorithms; specifically, K-Nearest Neighbor, Random Forest and the Model Ensemble method were used to develop predictive model that determined which twitter users in lived in Favelas with 98% accuracy.

Founder & Fashion Designer, Massey Ronica Nigeria March 2012 - May 2014

• Built dynamic financial model to determine the best price range for products and customer acquisition strategy by using regression models, resulting in a start-up grant of $50k; 100% growth in clientele within the first month; and 45% growth in the second year.

• Secured advertising deal with media company, saving the company 80% of advertising costs; negotiated with suppliers and sourced fabrics; trained staff on pattern making, increasing production efficiency and capacity by 50%.

• Identified fashion trends, created unique designs and drafted patterns; created first haute couture collection, resulting in an increase of clientele.

Projects

Current Project

Part of the student team that is developing the mobile app for Fordham University’s start-up hub called Fordham Foundry. My tasks are the backend design and setup of the database, and the frontend design of the signup page, using ReactNative, Android Studio and Firebase.

Past Projects

• Developed a predictive web application that determines if a breast tumour is benign or malignant given the preliminary results or measurements of the tumour. - https://enharry.shinyapps.io/CancerPredictor/

• Human Activity Analysis - http://rpubs.com/ENHarry/jawboneanalysis

• Air Pollution Analysis - http://rpubs.com/ENHarry/airpollution

• Storm Data Analysis - http://rpubs.com/ENHarry/stormdata

• Predictive Machine Learning - https://github.com/ENHarry/machine_learning/tree/gh-pages

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