LEO Lecturer for QMSS 301 Winter Term 2027

About this position

JOB OPENING ID: 285472 MODES OF WORK Onsite REGULAR/TEMPORARY: Regular ORGANIZATIONAL GROUP: College Of Lsa DEPARTMENT: LSA Quant Methods & SocSci Pgm How to Apply In order to be considered for this position, all applicants must apply to this posting through this website (the cover letter and CV must be uploaded as one document). Mission Statement The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future. Job Summary The College of Literature, Science, and the Arts, and the Quantitative Methods for the Social Sciences at the University of Michigan invite applications for a Leo Lec I position at 50% effort for the Winter Term 2027. This appointment is scheduled to begin on January 12, 2027 and end on May 7, 2027. Responsibilities* Duties of these Leo Lecturer I positions are expected to include teaching, developing course materials, evaluating and grading students, and holding regularly scheduled office hours. A typical full-time (100% effort) load for a Leo Lecturer I in the College of Literature, Science, and the Arts is three courses per semester. Full-time and part-time positions are available. Course Title(s): QMSS 301: Quantitative Social Science Analysis and Big Data Course Objectives: The role of this Lecturer I position will be to serve as GSI for 1 sections QMSS 301 for the Winter 2027 semester in lieu of a non-LSA graduate student instructor (GSI). Please see the course guide for discussion times and locations. QMSS 301: Quantitative Social Science Analysis and Big Data (at 50%) Required Qualifications* A PhD in a social science discipline with a demonstrated focus on quantitative methods is required. Experience teaching courses using quantitative methods and analysis, with demonstrated proficiency in teaching and/or using Microsoft Excel and R is required. Proficiency with multiple analytical tools and approaches, including Excel, R, and/or Tableau, is preferred. Successful candidates will have contemporary knowledge and experience in applying data analysis and data science skills to social science-oriented research and/or teaching, with experience teaching undergraduate students strongly preferred. Preference will be given to candidates who are social scientists with proficiency using a combination of Excel, R, and/or Tableau in all of the following: data cleaning, data management (i.e., codebooks), descriptive statistics, hypothesis testing, data visualization, data cleaning, and data communication for a wide range of audiences. Desired Qualifications* An ideal candidate for this position would have a strong academic background in a social science discipline (or a closely related discipline). Desired qualifications include prior teaching or discussion-leading experience, as the role requires independently managing a discussion section. Outstanding organizational and communication skills are desired for grading assignments, holding office hours, and collaborating closely with the lead instructor. Modes of Work Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes. Union Affiliation This position is covered under the collective bargaining agreement between the U-M and the Lecturers Employee Organization, AFL-CIO, which contains and settles all matters with respect to wages, benefits, hours and other terms and conditions of employment. Background Screening The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks. Background checks are performed in compliance with the Fair Credit Reporting Act. Contact Information Questions about applying for this position can be emailed to: qmss.chiefadmin@umich.edu Application Deadline Review of applications will begin immediately and continue until the position is filled. Deadline for applications is November 24, 2026 The anticipated date by which an offer will be made is no later than December 14, 2026, The appointment opportunity described in this posting is subject to final approval by the academic unit. U-M EEO Statement The University of Michigan is an Equal Opportunity Employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants, including protected veterans and individuals with disabilities.

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