Takuya Kitazawa

  • M.S. in Information Science and Technology, specialized in recommender systems and scalable machine learning.
  • 6+ years of hands-on industry experience as a full-stack software engineer, OSS developer, data scientist, machine learning engineer, and product manager.
  • Productizing machine learning and data analytics on Treasure Data Customer Data Platform, an enterprise big data analytics SaaS platform, by not only implementing the system but also translating business needs into technical problems.


10/2020 – Present

Senior Product Manager

02/2021 – Present

Treasure Data (Canada), Vancouver, BC, Canada

10/2020 – 02/2021

Treasure Data, Tokyo, Japan

  • Serving a product management role in the digital marketing, data analytics, and machine learning domain. Product features I was in charge of include: out-of-the-box data visualization, A/B testing, and predictive customer scoring.
  • Productizing solution templates in an in-house Treasure Boxes ecosystem to accelerate advanced, strategic use of rich customer data. I have also worked closely with the business development team to collaborate with the partners and develop the platform together.

02/2020 – 09/2020

Product Manager

04/2019 – 02/2020

Staff Engineer

07/2018 – 03/2019

Senior Engineer

Arm, Tokyo, Japan

(Spin-off Treasure Data as an independent organization)

As an engineer:

  • Evangelized the connection of big data, machine learning, data science, and IoT, both for company's internal and external audiences.
  • Worked closely with an internal sales engineering team and served as a data science consultant to accomplish clients' machine learning projects in a wide variety of industries, including retail, gaming, and online media.
  • Represented individual contributors in Arm's data business unit, and mapped out granular IoT-data integrated use cases and solution ideas through prototyping and customer-facing work with global teams.
  • Led the development of a brand-new Python SDK for an enterprise big data analytics platform, and renovated the surrounding data science ecosystem.

As a product manager:

02/2017 – 07/2018

Data Science Engineer

Treasure Data, Tokyo, Japan

(Acquired by Arm)

  • Regularly contributed to the development of Apache Hivemall, a scalable machine learning library running on Apache Hive and Spark.
  • Led the development of out-of-the-box machine learning applications from competitor analysis and requirement gathering to system implementation and customer onboarding.

08/2015 – 06/2016

Part-time Software Engineer

Rakuten Institute of Technology, Tokyo, Japan

In the research organization, I have worked on the development of recommendation algorithms for an online golf booking service. Based on a previous study, I have conducted further assessments and proposed improvement ideas in terms of both theory and practice.

02/2012 – 02/2013

Part-time Software Engineer


Contributed to the development of (1) PHP applications for an avatar-based social networking service, and (2) an iOS application for virtual trial fitting using an image blending algorithm named Poisson Image Blending.

10/2011 – 03/2013

Research Assistant / Web Developer

The University of Aizu, Fukushima, Japan

Led the development of a Ruby on Rails-based web application "Aizu Weather" for regional weather monitoring, accompanied by interactive geospatial data visualization using d3.js.


04/2015 – 03/2017

M.S. in Information Science and Technology

The University of Tokyo, Tokyo, Japan

Thesis: Persistently Cold-Starting Online Item Recommendation for Implicit Feedback Data

Advisor: Dr. Takayasu Matsuo

GPA: 4.0



  • R&D Intern at Silver Egg Technology (Dec 2016 – Jan 2017)
    • In-depth data analysis on customer's purchase dataset collected from a real-world e-commerce service.
    • Proposing a novel recommendation algorithm, which has been a part of my master's thesis, to achieve higher accuracy of recommendation in the long run.
  • Machine Learning Intern at Treasure Data (Aug – Sep 2016)
    • Implementing user-defined functions (UDFs) for state-of-the-art recommendation and anomaly detection techniques on Apache Hivemall.
    • PoC implementation of a next-generation anomaly detection system for multiple system metrics, collected from an enterprise big data management platform.

04/2011 – 03/2015

B.S. in Computer Science and Engineering

The University of Aizu, Fukushima, Japan

Thesis: User Modeling in Folksonomies: Relational Clustering and Tag Weighting

Advisor: Dr. Masahide Sugiyama

GPA: 3.97

Honors and Awards:


  • Served as a teaching assistant in a Numerical Analysis course, and thought Java coding of numerical methods to 20+ undergraduates (Fall 2014)
  • Participated in Security and Programming Camp 2011 to deepen knowledge in web security (Aug 2011)