New

Research Staff Assistant, Data Analyst

Columbia University
United States, New York, New York
Apr 12, 2025
Job Type: Support Staff - Non-Union Regular/Temporary: Regular Hours Per Week: 35 Salary Range: $40,400 - $41,000 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. Position Summary The Eco-Epidemiology Lab at Columbia University is seeking a full-time Data Analyst to support research on human mobility, tick exposure risk, and urbanization. This position will focus on analyzing GPS trajectory data and survey responses collected via The Tick App, a smartphone application designed to study human behaviors related to tick exposure risk. Established in 2001, the Department of Ecology, Evolution, and Environmental Biology (E3B) at Columbia University focuses on ecology, evolutionary biology, and environmental biology, which constitute a distinct subdivision of the biological sciences with its own set of intellectual foci, theoretical foundations, scales of analysis, and methodologies. The E3B community offers academic excellence in a range of natural and social science disciplines that are directly related to biodiversity conservation, including evolution, systematics, genetics, behavioral ecology, public health, business, economics, political science, anthropology, and public and international policy. This is a grant-funded position. Continuation of the role is contingent upon the availability of funding. Responsibilities This work is part of the project Measuring Tick Risk Along an Urbanization Gradient, which seeks to understand where and how people encounter ticks during daily outdoor activities and travel across urban landscapes. By integrating geostatistics, spatial modeling, and machine learning approaches, we aim to classify movement patterns and analyze their relationship with tick encounters. The insights gained will help inform strategies for preventing tick-borne diseases. Process and analyze GPS trajectory data and survey data collected via The Tick App. Classify human movement patterns using trajectory segmentation and clustering techniques. Apply geostatistical methods and spatial data analysis to identify environmental risk factors. Use machine learning (e.g., neural networks) to classify movement patterns and detect outliers. Develop interactive maps and data visualizations using GIS software (ArcGIS, QGIS, R). Assist in managing, cleaning, and integrating large spatial and temporal datasets. Collaborate with an interdisciplinary team of researchers and contribute to scientific publications. Minimum Qualifications High School Diploma or equivalent required. 0 -3 months of experience in a research environment. Other Requirements Proficiency in R and/or Python for data processing, analysis, and modeling. Strong experience with GIS software (ArcGIS, QGIS, R) for spatial data analysis. Familiarity with GPS trajectory analysis and mobility pattern classification. Experience with machine learning methods. Ability to work with large and complex datasets from epidemiological surveys and citizen science projects. Strong analytical and problem-solving skills. Interest in vector-borne diseases, epidemiology, and public health (preferred but not required). Equal Opportunity Employer / Disability / Veteran Columbia University is committed to the hiring of qualified local residents.