About the position
Background of the recruitment and description of the project We are seeking a candidate with expertise in data analytics and business analytics, particularly in quantitative analysis, data analysis, and econometric methods, with a strong ability to apply these approaches to business and management research and education. Work content and job description • Teach at the graduate level (MBA and DBA programs) and conduct research in English. • Lead the Data Analytics / Business Analytics courses and research programs. • Teach courses in quantitative analysis, data analysis, econometric methods, and related topics. • Participate in administrative tasks, including committee work, MBA/DBA admission, and program administration. Common to all Job Types Annual Salary : 6 million yen ~ Official qualification in specific field, etc. Minimum Qualifications: 1) Ph.D. or other doctoral degree in quantitative analysis, econometrics, data analysis or a related field from a recognized university. 2) Consideration given to applicants near completion of a PhD or other doctoral degree. 3) Potential for high quality research and effective graduate-level teaching in English. Desirable Qualifications: 1) A strong research interest in, and commitment to, the application of quantitative methods to business, economic, technological and social issues. 2) Published or forthcoming papers in international peer reviewed journals. 3) A demonstrated interest in teaching quantitative and data-analytic methods, with a strong application-oriented perspective. 4) Proven teaching ability at the graduate level. 5) Japanese language proficiency is highly desirable, but not required. 6)(a) For Professor and Associate Professor: established international publication record. (b) For Assistant Professor: solid pipeline of international publications. Common to all Job Types Tenured - Tenure-track Supplementary explanation of compensation [Social Insurances] Enrollment in Employment Insurance, Industrial Accident Compensation Insurance, Employees' Pension and Health Insurance Others Incomplete submissions or missing required documents will not be considered. Attached documents Application Form : Online Submission • Applications must be prepared in English. Send applications via Google Forms • Application Submission: https://forms.gle/5vrCpwPj2VRFHLLm8 • Submit the documents as listed in the "Documents to be submitted" section below. Make sure that your application is complete prior to submission. Incomplete applications will not be considered. • Prepare all the documents in PDF format, and include your full name as part of the file name. Please put all the documents in one Zip folder, and title the folder as “Firstname_Lastname.zip”. Documents to be submitted 1) Cover letter clearly stating how you satisfy the minimum and desirable qualifications and summarizing your research /teaching interests and reasons for wanting to join the faculty at Hitotsubashi University of Business School, School of International Corporate Strategy, Tokyo, Japan. 2) Digital soft copies of 3 representative papers (published or unpublished). 3) List of three professional references (names, affiliations, titles, and contact information including telephone numbers and email addresses) who are prepared to provide letters of recommendation. 4) Current curriculum vitae, including teaching experience and a list of undergraduate- and graduate-level courses taught, if applicable. 5) Copies of official transcripts of graduate education (official transcripts required upon hiring). 6) A list of courses taught at the graduate level, preferably with course and faculty evaluation scores. And a proposed syllabus for an MBA Data Analytics / Business Analytics course consisting of 12 sessions (including a final exam and/or project) and including grading criteria and reading materials. Selection Online interviews from October 21 to 30, 2026. Campus visit fly-outs in November, 2026 Notification of result Only candidate(s) who pass the initial documentation screening will be contacted for interview by phone or e-mail by October 20, 2026. If not contacted by this date, it indicates non-progression to the interview round.
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