Description

Position Description:

NYU London is currently recruiting for a part-time lecturer to teach A Survey of Data Science, a course sponsored by the College of Arts & Science at New York University. Teaching commences in the spring term (Jan-May 2026).

Course Description:

Data science is a relatively new discipline that is radically reshaping our world. This course is a one semester tour of data science highlights for non-majors and non-minors. Because it is for non-majors, there is room to design the course around the instructor's expertise. There is no assumed background in either math or programming. The lectures for this course will focus on covering conceptual aspects of the tools of data science and demonstrations of how data science can be used. The associated laboratory sections will focus specifically on direct application of what is being learned in lectures using Python code, with guided demonstrations by the section leader(s).

Upon completion of this course, students will:

have basic competence in using Python to manipulate and analyze datasets and enough statistical literacy to interpret commonly reported statistical measures and outputs.
have the ability to implement and understand linear and logistic regression models.
have a general understanding of the basic elements and purposes of machine learning, including entry-level familiarity with crucial terms.
gain a sense of how data science methods are being applied in the world, along with a general notion of the advantages and limitations of these methods.

Expectation of Hours:

This is a 4-credit class, which calls for total contact hours equaling about 35 hours. The semester is 15 weeks (14 weeks of teaching plus an exam week) and there are 2.5 hours of classroom instruction each week. In addition to the time required for course preparation, classroom instruction, and marking, the instructor is required to hold a minimum of one set 60-minute “office hour” at NYU London per week, during which time they will be available to meet with students.

Teaching information:

Instructors are encouraged to use a variety of pedagogical techniques. This typically includes a combination of lecture- and discussion-based class sessions, as well as the use of student activities, such as debate exercises, flipped classroom environments, and experimental simulations.

In addition to exams, instructors may use a variety of assignments to assess student comprehension of the course material. These may include online weekly homework, writing assignments, short student presentations, and in-class multiple-choice quizzes. Instructors may select the mix that is more appropriate to their teaching methodology.

Instructors should be prepared to teach in-person and simultaneously to be prepared for remote instruction should circumstances require it. NYU uses Zoom as its primary platform for remote instruction.

About NYU and NYU London:

Founded in 1831, New York University is the largest private university in the United States. The University has degree-granting campuses in New York, Abu Dhabi, and Shanghai and operates 14 global academic centers and research programs in more than 25 countries. NYU London is an undergraduate study abroad program of exceptional quality with teaching strengths across the curriculum. Our UK faculty, drawn mainly from local universities, has an excellent record in teaching and research. Classes are held at the NYU London centre at 265 Srand, London, WC2R 1BH. If you would like to learn more about our program please visit NYU London.

Qualifications

We are seeking candidates with a PhD in Computer Science or a closely aligned specialist area. It is expected that the post-holder will ideally have 2 to 3 years of experience teaching at the university level; experience teaching undergraduates studying at a US university is helpful.

The successful candidate should have the right to live and work in the UK prior to appointment.

Application Instructions

All candidates must submit the following: (1) a cover letter; and (2) a current C.V.

All applications must be made online through Interfolio ByCommittee at apply.interfolio.com/171813. If you are new to using Interfolio Faculty Search you may find the following guide useful: Job Applicant's Guide to Interfolio Faculty Search.

Applications, in the form of a C.V. and covering letter, should arrive by 22 September 2025.

Competitive salary. Terms and conditions will be discussed with the successful applicant. The successful candidate should have the right to live and work in the UK prior to appointment.

NYU London is an equal opportunity employer committed to equity, diversity, and social inclusion. We strongly encourage applications from under-represented individuals in the profession, across color, creed, race, ethnic and national origin, physical ability, and gender and sexual identity. NYU London affirms the value of differing perspectives on the world as we strive to build the strongest possible university with the widest reach.

Equal Employment Opportunity Statement

For people in the EU, click here for information on your privacy rights under GDPR: www.nyu.edu/it/gdpr

NYU is an Equal Opportunity Employer and is committed to a policy of equal treatment and opportunity in every aspect of its recruitment and hiring process without regard to age, alienage, caregiver status, childbirth, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual orientation, unemployment status, veteran status, or any other legally protected basis. All interested persons are encouraged to apply for vacant positions at all levels.

Sustainability Statement

NYU aims to be among the greenest urban campuses in the country and carbon neutral by 2040. Learn more at nyu.edu/sustainability

Part-time lecturer in Data Science

New York University