Adjunct Lecturer of Data Science
William & Mary

Job Info

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Position Number:

P1022W

Position Title:

Adjunct Lecturer of Data Science

Unit Mission Statement:

Data Science is the study and application of methods that extract knowledge
from frequently large, diverse sets of data. Data Science at W&M provides a
novel learning environment. We push students beyond methods and
towards critically considering the implications of big data and algorithms on
our society.

Position Summary:

The Data Science Program at William & Mary is recruiting a pool of applicants for possible adjunct teaching positions. Should funding for such adjunct teaching positions become available, the Program will contact persons in the pool whose credentials match our teaching needs. The pool will be accessed only when an opening arises. Your credentials will remain active for one year after the date you submit them. After one year, if you are still interested in adjunct teaching, you must reapply to this adjunct pool. Note that we are unable to hire applicants who are not already in the pool.

Required Qualifications:

Master's degree in Data Science, Computer Science, Mathematics, Statistics, or related discipline, or equivalent experience and qualifications is required, including published work that utilizes extensive big data analytics. In addition, must have at least one-year experience working in a related field. Strong oral presentation and communication skills.

Preferred Qualifications:

Ph.D., in Data Science, Computer Science, Mathematics, Statistics, or related discipline at the time when the appointment begins. Prior teaching experience and applied experience outside of academic settings is preferred.

Conditions of Employment:

Department:

3KEA10 Data Science

Location:

William & Mary

Job Open Date:

11/14/2024

Review Begin Date:

12/02/2024

Job Close Date:

12/02/2025

Open Until Filled:

Yes

Employment Category:

Adjunct

Special Application Instructions:

Applicants must apply online at https://jobs.wm.edu. Submit a curriculum vitae, a cover letter, a statement of teaching interests that describes your approach to teaching and mentoring and that may also incorporate a discussion of how your past scholarly work informs your approach. Your candidate teaching statement may be included in your cover letter. Candidates are encouraged to reflect on their past experiences or future plans to foster an inclusive and welcoming climate for learners/scholars in Data Science in any of the aforementioned required documents. You cannot submit a separate diversity statement. You will be prompted to submit online the names and email addresses of three references who will be contacted by the system with instructions for how to submit a letter of reference. Review of applications is ongoing.

Background Check Statement:

William & Mary is committed to providing a safe campus community. W&M conducts background investigations for applicants being considered for employment. Background investigations include reference checks, a criminal history record check, and when appropriate, a financial (credit) report or driving history check.

EEO Statement:

William & Mary values diversity and invites applications from underrepresented groups who will enrich the research, teaching and service missions of the university. The university is an Equal Opportunity/Affirmative Action employer and encourages applications from women, minorities, protected veterans, and individuals with disabilities.

Benefits Summary Statement:

William & Mary offers our employees a full array of benefits including retirement, health insurance with options for expanded dental and vision along with group and optional life insurance with coverage for spouse and children, flexible spending accounts, and an EAP (Employee Assistance Program).

Our employees enjoy additional university benefits such as educational assistance, professional development, wellness benefits, and a robust holiday schedule. All employees have access to fitness facilities on campus. Staff members also have access to the university libraries, and much more. To learn more, go to: https://www.wm.edu/offices/uhr/benefits/index.php?type=none

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