Arakawa, Tokyo, Japan
Having completed my M.Sc. in Mathematics with a focus on Biostatistics at the Technical University of Munich—an institution widely regarded as Germany’s most rigorous and top-ranked technical university—I am eager to transition back to the field of Biostatistics. While I last served as an Actuarial Analyst at WTW, I am looking to transition into a Biostatistics role in Tokyo that aligns with my advanced research in clinical data and risk prediction. My technical foundation includes a master’s thesis on prostate cancer modeling and expert-level proficiency in Python, R, and SQL. Having previously studied at Osaka University and attained JLPT N1 fluency, I possess the professional linguistic skills and cultural experience necessary to thrive in the Japanese workspace. I am eager to apply my rigorous mathematical training from a world-class institution to contribute to innovative clinical research and data-driven healthcare solutions in Japan.
As an analyst at the retirement business unit, I managed pensioner data systems and put together pensioner obligation financial numbers for our clients' yearly financial statements. This involved administering and optimizing database systems using SQL and C++, programming automatic reports to be sent to pensioners, making pensioner calculations using insurance mathematics, and various data-driven tasks, adapting to the needs of the clients.
As an assistant to the Vice Dean of Talent Management and Diversity, I hosted events celebrating and promoting diversity at the TUM School of Computation, Information and Technology. Additionally, I managed the deanery’s website and evaluated statistics to highlight the diversity issues the school faces.
As part of my placement in a research division, I set up a Python test environment for the automatic evaluation of algorithmic and AI solutions. This included setting up data pipelines, defining metrics, and generating visualizations. The testing environment was set up with a high level of independence, assisting the research team in getting quick and valuable feedback on any changes in the algorithms.
As part of a team researching uncertainty quantification in neural network-based systems, I im- plemented, tested, analyzed, and compared different algorithms and state-of-the-art metrics for generating uncertainty scores in neural networks. A special focus of my research was on combining methods from the areas of deep learning and classical statistics. In the last months of my employment, I composed my Bachelor’s thesis in cooperation with the institute. My work at the institute helped by providing a comparative overview of a whole area of research while also testing a new, innovative approach against the existing research.