Lecturer/Senior Lecturer in Discipline – Actuarial Science

Lecturer/Senior Lecturer in Discipline – Actuarial Science

The School of Professional Studies (SPS) at Columbia University seeks to fill two positions for a Lecturer/Senior Lecturer in Discipline to serve as core faculty members in SPS's MS Program in Actuarial Science. Senior Lecturers in Discipline are expected to have substantial experience and accomplishments, and a superlative record of teaching as a lecturer, and documented evidence of pedagogical excellence in carrying out administrative or other department responsibilities. Lecturers in Discipline are expected to have teaching experience, documented evidence of pedagogical excellence, and evidence of professional growth and activity in the given field. These are full-time, non-tenure-track appointments with multi-year renewal contingent on successful reviews. The positions are effective July 1, 2017.

The Actuarial Science program seeks individuals with a vibrant portfolio of academic study, experience and publications in one or more of the following disciplines as it relates to actuarial science:

  • Life insurance

  • Health insurance

  • Pensions and retirement systems

  • Property and Casualty insurance

  • Reinsurance

  • Enterprise Risk Management and/or Investments

    Teaching three actuarial science courses per semester and advising in the MS Actuarial Science program and related programming areas is expected, in addition to the following: active participation in curriculum and program development and evaluation; faculty recruitment and evaluation; and participation in the development and execution of strategies to support program area students as they transition from prospect to alum; academic and career advising to support the academic needs and professional aspirations of the MS students. The ideal candidates will hold a PhD degree in statistics, data science, applied statistics, actuarial science, or a related field. The candidates must be capable of contributing to the program's academic mission, and demonstrate the potential for vision and direction that will be required for all aspects of the position. International teaching and/or professional experience is preferred but not required.


Minimum Qualifications:

All applicants MUST meet these minimum qualifications to be considered for the position.

  • Associateship or fellowship from a major actuarial organization (Society of Actuaries, Casualty Actuarial Society, or other internationally recognized professional actuarial association) required.

  • Candidates must have demonstrated experience in their areas of professional practice and accompanying pedagogy.

  • Actuarial science teaching experience required.

Preferred Qualifications:
Extensive leadership experience applying these disciplines across a wide spectrum of industries/sectors preferred; and deep and demonstrated understanding of the academic and applied trends that are driving best practice and research in this emerging cross-disciplinary field of study.

  • Doctorate degree required in statistics, data science, applied statistics, actuarial science, or related field strongly preferred

  • 10+ years' experience in the field of actuarial science

  • Experience conducting applied research

  • Global professional and/or teaching experience

  • Extensive professional network

  • Experience teaching online

Review of candidates begins on January 1, 2017 and will continue until the position is filled. All applications must be made through Columbia University's online Recruitment of Academic Personnel System (RAPS).

Please upload the following required materials into RAPS:

  • cover letter

  • CV

  • teaching evaluations

  • statement of teaching philosophy

  • one writing sample, and

  • 3 letters of recommendation, which will be solicited from a list of references you provide.

For more information, and to apply, please go to: academicjobs.columbia.edu/applicants/Central?quickFind=63820

Columbia University is an Equal Opportunity/Affirmative Action employer --Race/Gender/Disability/Veteran.