"Associate Research Scientist"

Overview

Reporting to the Senior Research Scientists, the Associate Research Scientist will provide research support to the New York City Longitudinal Study of Wellbeing (NYCLSW) study, within the Poverty Center at the Columbia School of Social Work, which conducts longitudinal surveys of panels of New York City residents with a focus on the causes and consequences of economic disadvantage. The primary responsibilities for this position include: data collection, data management, and data analysis/report‐writing. In collaboration with a field team of survey coordinators and interviewers, the incumbent will take primary responsibility for field data management using Voxco and Stata, and will participate in high-level planning for project research and organization. The Associate Research Scientist also has specific responsibility for the NYCLSW Chinese Over‐Sample. As such, it requires fluency in Mandarin/Chinese and knowledge of New York City’s Chinese‐origin communities, and understanding of sample recruitment and retention practices used with hard‐to‐reach populations.

REAPPOINTMENT IS CONTINGENT ON FUNDING AVAILABILITY.

Responsibilities

1. Take primary responsibility for field data management on the NYCLSW study (40%)
   • Work with the field director to plan and monitor the pace of fieldwork
   • Drawing on expertise in survey methodology and data analysis, develop methods for evaluating the efficiency of the NYCLSW field protocol, increasing survey retention, reducing missing data, and improving data quality
   • Take a lead role in field data management, using Voxco and Stata to maintain field databases, generate survey panel files, and work with the survey coordinators as needed to implement the fieldwork
   • Identify technical tasks which can be shared with full-time research staff or delegated to student employees; conduct any needed training, mentoring and documentation; and oversee any technical work that is delegated to field staff
2. Oversee fieldwork for the NYCLSW Chinese oversample (30%)

   The incumbent will lead the fieldwork for the Chinese‐origin oversample (COS) of the NYCLSW. This work includes developing survey items to capture the distinctive experiences of Chinese-origin New Yorkers, conducting qualitative interviews with study participants in this sample, and overseeing survey data collection. As needed, the incumbent will develop and evaluate distinctive recruitment and retention strategies for this hard-to-reach sample.

3. Participate in data analysis and report/article writing (20%)

   The incumbent will work with faculty and research staff to plan and conduct analysis of NYCLSW survey data and to write reports and academic publications based on these analyses.

4. Other duties as assigned (10%)

   The incumbent will take on other responsibilities as needed. Examples might include participation in big-picture planning for project data collection; identification of new topics for inclusion in the survey; development of funding proposals to support new study components.

   Supervises student research assistants and interns.

Qualifications

• PhD in Social Work, Sociology or related discipline
• Four years of experience conducting social science research.
• Strong research, interpersonal, teamwork, supervisory, and organizational skills
• Strong written and oral communication skills
• Strong data management and analysis skills, including multivariate analysis and use of survey weights
• Proficiency with Voxco survey software and Stata
• Expertise in survey methodology and extensive experience with survey‐based data collection
• Knowledge of New York City’s Chinese-origin communities
• Fluent in Mandarin/Chinese

Columbia University is an Equal Opportunity Employer / Disability / Veteran

Pay Transparency Disclosure
The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University’s good faith and reasonable estimate of the range of possible compensation at the time of posting.