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Machine Learning, Ads and Deep Learning
PAST I got my undergraduate degree from the University of Pittsburgh. And I pursued my dream at UCLA's graduate program before I realized I am more interested in the data science field. Then, I got a master degree at UCLA Anderson School of Business. Besides business-driven courses, I took convex optimization, a bunch of math, and statistics classes. Then, I moved to Toronto to join Ritual, a food pick-up platform company, as a data scientist. 1. I worked independently to set up a one-stop statistical engine for campaign analysis. The engine connects with the production database by an ETL pipeline and exposes calculated results to internal users via a friendly UI, which reduces analysis time from 2 hours to a few minutes. 2. I worked with marketing teams to prepare marketing campaigns, analyzing data and conducting rigorous causal analysis. 3. I worked with product teams on product launch and research. I conducted multiple experiments via a frequentist approach and Bayesian hypothesis testing. 4. I worked with the business teams to provide fast data analysis support via Spark and Python. 5. I mentored junior team members. We worked collaboratively on projects like customer lifetime value estimation, recommendation systms, business unit classifier, etc. NOW I am a Sr. Data Scientist at Canadian Tire's marketing team. I am productionizing deep learning techniques to help the company to get more clarity about our products. I combined techniques like graph-based embedding, computer vision, and natural language processing to calculate product similarities in our system. Additionally, I am working on an experimental platform at Canadian Tire. I applied both traditional A/B/N experimental design and execution techniques and multi-armed bandit techniques to increase experiments' efficiency. CODING I love statistical and mathematical programming. I have more than 5 years'
Georgia Institute of Technology
Master of Science, Computer Science
January 1, 2022 – July 1, 2024
UCLA Anderson School of Management
Master of Science - MS, Data Analytics
January 1, 2017 – January 1, 2018
UCLA
Theoretical and Computational Chemistry
January 1, 2016 – January 1, 2017
University of Pittsburgh
Bachelor's degree, Chemistry
January 1, 2012 – January 1, 2016
Yelp
Sr. Applied Scientist
May 1, 2024 – Present
Remote
Yelp
Sr. Data Scientist
June 1, 2022 – May 1, 2024
Remote
Wealthsimple
Data Scientist, ML
September 1, 2021 – June 1, 2022
Toronto, Ontario, Canada
Canadian Tire Corporation
Sr. Research Data Scientist
March 1, 2020 – September 1, 2021
Toronto, Ontario, Canada
Ritual.co
Data Scientist
February 1, 2019 – March 1, 2020
Greater Toronto Area, Canada
CMT Level II Candidate
CMT Association
June 23, 2026 – Present
CFA Level II Candidate
CFA Institute
June 23, 2026 – Present
Cultural Fit Analysis
The candidate has worked in diverse company sizes and industries (Yelp, Wealthsimple, Canadian Tire, Ritual.co), indicating adaptability. Their progression from Data Scientist to Sr. Applied Scientist shows ambition and growth. The multiple Master's degrees and certifications (CFA, CMT candidate) suggest a strong drive for continuous learning and professional development. However, the target role is 'Data Analyst', which might be a step down from their 'Sr. Applied Scientist' role, potentially indicating a mismatch in career trajectory or expectations for the specific role.
Soft Skills & Operational Fit
The candidate's resume descriptions indicate experience in collaborative environments (working with product, marketing, operations teams) and mentoring junior team members, suggesting good communication and leadership potential. The focus on deploying models and building frameworks implies a structured and operational mindset. However, without specific soft skill assessments or interview data, a definitive operational fit cannot be fully determined.