Graduate Assistant

Barnard College • New York City, NY

7h • Onsite

About The Position

The Graduate Assistant at Barnard’s Empirical Reasoning Center (ERC) will assist ERC staff in supporting students, staff, and faculty in engaging in empirical analysis. Specific research and course needs shift each semester, and the Graduate Assistant will flexibly help the ERC staff to address and support those needs. The ERC seeks GAs to support its mission of advancing empirical reasoning, data literacy, and inclusive data practices across the Barnard curriculum. GAs will contribute to instructional support, workshop development, student consultation, and programmatic initiatives that strengthen the ERC’s role in applied quantitative, qualitative, and spatial learning. We want candidates who are eager to further develop as instructors, analysts, and applied practitioners while contributing meaningfully to curricular and co-curricular initiatives. GAs will work closely with the Senior Associate Director and Associate Director to align their instructional and programmatic contributions with ERC priorities. Each GA will specialize in one of three areas (quantitative methods, GIS and spatial analysis, or data for social impact). Through sustained engagement in consultations, workshop facilitation, course support, and program implementation, GAs deepen their technical expertise, expand their instructional capacity, and gain experience translating complex analytical methods into accessible learning environments. In doing so, they strengthen both their own professional competencies and the ERC’s ability to meet growing instructional and programmatic demand. We are hiring two GA's each with a different focus areas: Statistical Methods & Quantitative Methods GA This GA will focus on strengthening the ERC’s statistical consulting and quantitative instructional support, including applied modeling, reproducible workflows, and advanced data analysis methods. GIS & Spatial Analysis GA This GA will focus on geospatial technologies and spatial methods, supporting classroom integration of GIS and spatial analysis across disciplines and advancing spatial literacy within the curriculum.

Requirements

• Experience with teaching undergraduates
• Intermediate to advanced knowledge of at least one core technology at the ERC (R, Stata, ArcGIS, QGIS)
• Experience with course preparation and management
• Strong problem-solving and analytical skills, with experience in statistical modeling
• Willingness to learn and implement new technologies and workflows
• Understanding of inclusive pedagogy and accessibility in instruction
• Ability to work independently and as part of a team
• Strong organization skills and attention to detail
• Strong communication and interpersonal skills
• Must currently be a student in a Graduate Program

Nice To Haves

• The ideal candidate will be detail oriented with a strong work ethic, have both excellent quantitative skills and communication skills, and will be comfortable thinking critically about quantitative data.

Responsibilities

• Provide one-on-one and small-group support to students during open lab hours, assisting with coursework and research projects involving tools such as Excel, Stata, R, Python, GIS, and SPSS.
• Design and teach workshops in support of ERC curricular initiatives.
• Contribute to ERC events and programs from planning through assessment.
• Maintain documentation and assist in the continued development of instructional resources.
• Develop their expertise in applied empirical methods and instructional practice through consulting, workshop design, and course support.
• Present ERC-related instructional innovations or applied projects at academic or professional conferences.
• For events and programming, the GA will focus on supporting and expanding ERC programming that connects data analysis to questions of public impact and responsible data science.
• The role includes contributing to workshops, collaborative programming, and curricular initiatives that center ethical data practice, algorithmic accountability, and structural analysis.

What This Job Offers

• Job Type: Part-time
• Career Level: Entry Level