KEVIN YANG

[ addcib@r.postjobfree.com Ó 226-***-**** Kevin Yang

EDUCATION

Statistics and Economics Majors

University of Toronto

Sep 2017 – Apr 2021 (Expected)

SKILLS

Languages

Python R Java

JavaScript SQL

Technologies

MS Office NumPy Matplotlib

Seaborn Pandas Plotly

SVN Github

ML Techniques

Linear/Logistic Regression

K Nearest Neighbors

Decision Trees K Means Clustering

Cloud Technologies

Azure AWS

EXTRACURRICULAR

Event Executive

Canadian Asian Student Society

Sep 2019 – Present

Executed events to bring students

together and create a community on

campus

COURSEWORK

Relational Databases and Web Dev:

SQL to query data

HTML/CSS/JS to build a website

Stochastic Processes:

Markov Chains

Gaussian Processes

Brownian Motion

EXPERIENCE

Product Data Analyst

Humi

May 2019 – Aug 2019 Toronto, ON

Designed reports tracking KPI health (Net MRR Churn Rate, NPS, Retention Rates) This enabled the Client Experience team to iden- tify engagement trends and prevent churn

Implemented Python scripts on top of SQL to effectively query data from the Humi database in any format and layout required

Created a Net MRR Churn deck to show members of the Client Experience team their core and at-risk clients. This displayed each member’s monthly portfolio growth/decline.

Discovered a discrepancy between NPS scores given by users and power users, this initiative was proactive churn prevention and was credited with addressing 50% of all churn. This tool enabled churn to be minimized

PROJECTS

Analysis of Bank Stocks - Financial Crisis 2016

May 2020

Collected, pre-processed, and analyzed large sets of Financial Cri- sis data obtained through data mining the web

Designed cluster heatmaps to outline correlation between Bank stock closing prices, displaying market behaviour patterns

Leveraged line plots to showcase market trends for the desired time period, utilizing close price data. This presents a huge crash for Citibank in 2009 due to the Obama Inauguration. Tools: Pandas Data reader, Pandas, Seaborn, Numpy, Cufflinks Optimizing Transportation in Populated Areas - ML Approach

Present

Trained machine learning models using live-feed street intersec- tion video to successfully implement object detection, pathing, and human count for storefront traffic

Designed and executed an informative platform for the average resident/tourist. With a motivation from the user, the platform recommends hot spots in any area of interest

Tools: OpenCv, Keras, Tensorflow

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