Summary

A highly motivated and analytically driven individual with a strong foundation in data science, quantitative analysis, and statistical rigor. Certified at the highest level in Statistics (Japan Statistical Society Certificate, Grade 1), I bring advanced analytical skills to ensure accuracy, transparency, and reliability in complex financial and business contexts. My academic research, internationally recognized and presented at leading conferences, demonstrates my ability to apply AI and data-driven methodologies to solve real-world issues with measurable impact. As a visiting researcher at the University of California, Davis, I have expanded my global perspective and honed my ability to collaborate across cultures and disciplines.

While my academic focus has been healthcare AI, my core strength lies in breaking down multifaceted problems, applying structured analysis, and delivering precise, evidence-based insights—skills directly aligned with auditing and assurance services. I am particularly drawn to Azusa Audit Corporation’s reputation for upholding the highest standards of integrity and transparency while supporting clients in building sustainable and trustworthy businesses.

Fluent in both Japanese and English, I thrive in global, cross-functional teams and am eager to contribute to Azusa Audit Corporation’s mission of strengthening corporate governance and trust through rigorous audit practices and data-driven insights.

Skills

  • Statistics

    JSSC Grade 1

  • Technical Skills

    Python, SQL, Java, C

  • Languages

    Japanese (Native), English (Fluent – TOEFL 87)

Education

Keio University

Faculty of Science and Technology - Bachelor of Computer and Information Science

2021 - 2025

GPA: 3.56

Graduated: March 2025

University of California, Davis

Electrical and Computer Engineering - Visiting Scholar

2025 - 2026

I will be engaged in research at UC Davis as part of the Aspire project

Keio University

Faculty of Science and Technology - Master of Computer Science

2025 - 2027

GPA: 3.38

Expected Graduation: March 2027

Research

47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Efficient and Effective Fine-tuning Method for Depression Detection from Conversation

Role: First-author / Presenter

Work Experience

pluszero

Internship

March 2022 - Now

Developed a machine-learning driven app to support textbook-based study, improving recommendation logic via user behavior analysis.

Led UX improvement through user feedback sessions, collaborating with design and content teams.

Motivation

I am motivated to pursue a career in consulting, where I can leverage my statistical expertise and research experience to solve multifaceted business challenges. My academic background has trained me to analyze data critically, design effective methodologies, and communicate results in a clear and actionable way. Guided by curiosity and a strong work ethic, I am eager to tackle demanding projects and collaborate with diverse teams to deliver innovative, data-driven solutions. I am determined to contribute long-term value to clients while continuously expanding my knowledge and skills.