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Adjunct Faculty: MS in Data Analytics and Policy

Job in Washington, District of Columbia, 20022, USA
Listing for: Inomics
Full Time position
Listed on 2026-10-16
Job specializations:
  • Education / Teaching
    University Professor, Academic, Data Scientist
Salary/Wage Range or Industry Benchmark: 85440 - 95460 USD Yearly USD 85440.00 95460.00 YEAR
Job Description & How to Apply Below

Adjunct Faculty: MS in Data Analytics and Policy

Requisition #: A-192459-42
School:
Zanvyl Krieger School of Arts and Sciences

Location:

Telecommute, DC
Position Type:
Faculty
Shift Type:
Part Time
Salary Range: $7,120
Closing Date:
Open until filled

General Description

Institution

Description:

Advanced Academic Programs (AAP) is a division of the Johns Hopkins University's Krieger School of Arts and Sciences. As part of the nation's first research university, AAP offers high-quality master's degrees at its Washington, D.C., Center, at JHU's Homewood Campus in Baltimore, Maryland, and online. AAP distinguishes itself through its intensive instructional assistance, selective admissions, and 60 dedicated full-time faculty. Tenured Krieger School faculty members serve as program chairs to oversee the academic rigor of AAP's graduate offerings.

JHU is committed to hiring candidates who, through their teaching and service, will contribute to the diversity and excellence of the academic community. For more information, see https://advanced.jhu.edu/ .

The Advanced Academic Programs (AAP) division seeks non-tenure-track adjunct faculty to teach courses within the M.S. in Data Analytics and Policy program. The course(s) will be taught online. Specifically, the program seeks candidates with experience teaching foundational computational skills for data science, including R, Python, and database management. Candidates with specific expertise integrating AI and LLM tools into programming courses are of particular interest, as are instructors experienced in online course development and teaching.

Candidates will teach and engage students from diverse backgrounds.

The expected salary range for this position is: $7,210.

The referenced salary range is based on Johns Hopkins University's good faith belief at the time of posting. The actual compensation offered to the selected candidate may vary and will be based on factors including, but not limited to, the experience and qualifications of the selected candidate - e.g., years in rank, training, field, discipline, other work experience, and other similar factors;

geographic location; internal equity; external market conditions; and other factors as reasonably determined by the University.

Qualifications

Minimum Qualifications
  • Master's degree with training in quantitative statistical methods (e.g., political science, sociology, business analytics, economics, geography, public policy, psychology, or similar)
  • Demonstrated experience using R and Python for programming, data visualization, and statistical analysis
Preferred Qualifications
  • A terminal degree with training in quantitative statistical methods (e.g., political science, sociology, business analytics, economics, geography, public policy, psychology, or similar)
  • 1-3 years of graduate-level teaching experience
  • Online teaching experience
  • Training in statistical programming and analysis using R and Python
  • Professional experience in applied statistics, predictive modeling, machine learning, database management, and related data science topics
  • Teaching evaluations for the two most recently taught courses

The selected candidate will be expected to undergo a background check, submit proof of educational attainment, and submit references upon request.

Total Rewards

Johns Hopkins offers a total rewards package that supports our employees' health, life, career and retirement. More information can be found here: https://hr.jhu.edu/benefits-worklife/ .

Equal Opportunity Employer

The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. To that end, the university does not discriminate on the basis of sex, gender, marital status, pregnancy, race, color, ethnicity, national origin, age,…

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