Adjunct Instructor, Data Analysis & Visualization

About the role

The School of Sciences and Humanities at Wentworth Institute of Technology is seeking an instructor to teach a data analysis and visualization course during Summer 2027.

Summer Semester: May 5 - August 11, 2027

Meeting Time: Evenings

Preferred Modality: In person

Also Considered: Online synchronous instruction

We particularly welcome instructors with experience using data and visualization in social science or humanities inquiry, including survey design, evaluating and interpreting evidence, recognizing bias and limitations in data, and communicating data-informed findings clearly and ethically. Familiarity with accessible data analysis and visualization tools used to support this work is desirable.

Interested instructors should be comfortable guiding students through a semester-long social inquiry project that moves from defining a meaningful question and considering appropriate evidence through analysis, interpretation, visualization, and communication to an intended audience.

Official Course Description

Regardless of profession, being able to gather, analyze, and visualize high quality data to gain insight into an issue and successfully articulate your findings to key decision-makers makes you a more valuable asset.

This course takes a holistic approach to data-driven decision-making by introducing the theory, practice, and ethics of effective project and audience definition: data collection and survey design; data scraping, blending and cleaning; data analysis and visualization using a variety of software applications.

You will leave this course with improved abilities to collect, analyze, and visualize data - and in a way that has integrity and validity and that successfully engages your audience.

Required Qualifications and Teaching Approach

• We seek a social scientist or humanities scholar with a master's degree or doctorate (MS, MA, MEd, PhD, or EdD) in psychology, sociology, political science, anthropology, communications, history, economics, or another social science or humanities field.
• A qualifying graduate degree in a social science or humanities field is required. Applicants whose degrees are exclusively in computer science or other technical fields will not be considered.

This is not a Data Science or computing course. Technical tools are used in service of social science and humanities inquiry and the University's general education goals. The emphasis is on asking meaningful questions, evaluating sources and evidence, understanding sampling and bias, interpreting findings in context, and communicating conclusions responsibly.

This is an introductory general education course, not a technical Data Science course, designed for students with no prior experience in the relevant disciplines, data analysis, or data visualization. The instructor must be able to make foundational concepts accessible and help students use appropriate tools in support of inquiry, interpretation, and communication. No prior programming or advanced quantitative background should be assumed.

Instruction must advance general education learning objectives in critical information literacy, critical thinking, communication, and ethics. Students should learn to evaluate data sources, ask meaningful questions, recognize bias and misleading representations, consider ethical responsibilities, and communicate findings clearly.

The emphasis should remain on critical inquiry, interpretation, ethical reasoning, and communication rather than on developing advanced computational or programming skills.

Because of employer feedback, Microsoft Excel should be among the instructional tools, helping students develop practical data literacy relevant to employer expectations. Students should receive introductory experience using Excel to organize and examine data and to create clear visual representations that support interpretation and communication. Other accessible tools may supplement Excel where they support the course's general education learning goals. The course does not require advanced programming, computational modeling, or advanced Data Science methods.

We welcome experience with a scaffolded approach to social inquiry and data literacy, including helping beginners formulate questions, evaluate data sources, consider sampling and bias, analyze and interpret evidence, create effective visualizations, and communicate findings clearly and ethically.

The instructor should be comfortable guiding beginner students with diverse needs through a manageable, semester-long inquiry-based project, with structured practice and feedback at each stage: defining a meaningful question, identifying and evaluating appropriate evidence, conducting accessible analysis, interpreting findings, creating effective visualizations, and communicating conclusions to an intended audience.

Expectations for Online Instruction

If the course is offered online, the instructor must have demonstrated ability to deliver high-quality, engaging synchronous online instruction. The online course should provide a level of interaction, structure, feedback, and student support comparable to an in-person course.

The instructor should be comfortable teaching software-based skills remotely, including demonstrating tools such as Microsoft Excel, guiding students through hands-on exercises, troubleshooting common difficulties, and supporting students with varied levels of technical confidence.

The instructor should also be prepared to teach effectively in an AI-enhanced teaching and learning environment. This includes helping students use generative AI and other emerging tools thoughtfully and responsibly where appropriate, while maintaining expectations for data integrity, critical thinking, ethical use of information, appropriate attribution, and independent student learning.

Because critical evaluation of information and data is central to the course, the instructor should be prepared to help students critically evaluate AI-generated analyses, visualizations, interpretations, and claims rather than accepting them uncritically.

Ideal Candidate

The strongest candidate will be a social scientist who uses data as a tool for inquiry, critical thinking, and communication and who can make quantitative and visual concepts approachable for beginners. We are particularly interested in instructors who can help students think critically about how data are produced, selected, interpreted, visualized, and communicated, including questions of bias, ethics, validity, and potentially misleading representations.

The successful instructor should approach software and technical tools as means of supporting inquiry rather than as the primary subject of the course. The emphasis should remain on critical information literacy, ethical reasoning, interpretation, visual communication, and applied learning.

Position Details

At this time, the university is unable to sponsor applicants for H-1B visas.

Adjunct faculty compensation varies based on instructional mode (lecture or lab), number of course credits, and program. The minimum adjunct rate is $1,474 per credit.

Compensation and Benefits

• Wentworth Institute of Technology is committed to fair, transparent, and legally compliant compensation practices. We believe that clarity about pay structures and ranges supports equity, fosters trust, and ensures a positive workplace for all employees.
• Please visit here to see the comprehensive benefits package offered to support the best experience for our employees.

Inclusive Excellence at Wentworth

Inclusive Excellence is one of the four pillars of the Strategic Plan. Actively and intentionally cultivating a diverse and culturally competent institution where each member has the opportunity and support to reach their full potential and make contributions to our campus community and beyond is Inclusive Excellence at Wentworth.

All applicants have the right to accessibility support and accommodations. To request accessibility support or accommodations, contact the Executive Director of Equity and Compliance, Catlin Wells, at.