Kalibrr / Product Analyst
Accuracy in predicting “Aha” Moment
Improved “Aha Moment” prediction from 65% to 80% accuracy for new feature by implementing tree-based machine learning model in Python
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FlashCampus / Co-Founder
An Undergraduate Student in Japan with considerable experiences in Products, Data Science & Analytics, and Software Engineer. Passionate in Developing Tech-based Product that meets Business and Consumer needs.
Highly interested to utilize and advance personal skills through active and impactful contributions for others.
Lead engineer and designer in Agile methodology to build mentoring and information platform using Next.Js and MongoDB. Collaborated with engineer using GitHub to build mobile-responsive website using Next JS with registration, search, save, personalization, email sending,
Business Analytics Digitalization from optimizing price with machine learning, extracting insight from s billions of row and ~50GB size data using PySpark in Azure DataLake, to building analytics dashboard with Dash and Plotly
Monbukagakusho Scholarship Awardee
Proposed product strategy from analyzing and visualizing millions of rows of data using Bigquery and SQL in Google Cloud Platform
Leading a team of 7 in conducting usability testing and user research to research users needs and user experiences. Analyzing google analytics, research data, market condition, formulating User Journey, User Persona, and revamping User Experiences. Giving value proposition, marketing strategy, and user experience & interface recommendatio
First startup in MEXT Scholarship preparation. Conducting product & market research. Planning & implementing business & marketing strategy. Gaining 120,000 yen profit and 350 instagram followers in only about one month.
Kalibrr / Product Analyst
Improved “Aha Moment” prediction from 65% to 80% accuracy for new feature by implementing tree-based machine learning model in Python