We are seeking a skilled and motivated Data Analyst to support a longitudinal research project examining the relationship between opioid use, ART (antiretroviral therapy) adherence, and viral load management among people living with HIV in Harlem, NY. The goal of the study is to analyze patterns in opioid use and how they affect HIV health outcomes, while controlling for factors such as mental health, housing instability, and other social determinants of health. The research will draw from a comprehensive dataset, including client intake forms, service records, and self-reporting surveys.
The purpose of this role is to clean, organize, and analyze the data, then report your findings. The initial timeline for the role is two weeks. This position is ideal for a recent graduate seeking practical experience in data analysis.
Key Responsibilities:
Data Collection and Management: Assist in extracting, cleaning, and managing baseline and reassessment datasets.
Data Cleaning and Standardization: Identify inconsistencies, resolve missing values, and standardize data formats for accurate analysis.
Statistical Analysis: Use statistical methods, particularly regression analysis, to examine the relationships between opioid use severity, ART adherence, and viral load levels.
Data Visualization: Create clear and insightful data visualizations (e.g., charts, graphs) to communicate findings to the research team and stakeholders.
Reporting: Collaborate with the research team to generate summary reports of findings, and assist in drafting sections of research papers or presentations.
Required Qualifications:
Proven experience with data analysis, preferably with large datasets.
Proficient in Excel, strong knowledge of statistical software a plus.
Familiarity with regression analysis and correlation coefficients.
Ability to clean and standardize data, identify and resolve inconsistencies, and apply imputation techniques where needed.
Excellent attention to detail and problem-solving skills.
Strong communication skills for presenting data findings.
