Programme: Neurodevelopment and AutisM in South ASia Treatment and Evidence(NAMASTE)
Reports to: Project Director
Tenure: 36 Months(approx)
Time: Full time (5 days a week)
Selection Process: Written exam and Interview

About the Project:

NAMASTE is a research project which aims to design and implement a flexible evidenced pathway towards universal health coverage for children with autism, through a program of research, training, and capacity building across India, Sri Lanka and Nepal. This is a collaborative research project, led by the University of Manchester in the UK and India, Nepal and Sri Lanka. In Nepal, the ACNS collaborates to conduct this project in Godawari Municipality, Lalitpur district. The major objectives of the NAMASTE project are as follows:

• Enhance the capacity of staff and non-specialist service providers working incommunity level health posts for early detection of children with neurodevelopmental disorders and autism
• Provide an evidence-based intervention for parents and caregivers to address the unique, behavioral, intellectual and communication needs of children with neurodevelopmental disorders and autism
• Develop community engagement materials for public awareness in Nepal in collaboration with families and self-advocates to improve access to care and intervention for neurodevelopmental disorders and autism

About the Role:

ACNS is seeking to recruit a Research Associate (Data Management and Analysis) for NAMASTE with expertise in Python or R to support data management. The ideal candidate will be responsible for data cleaning, analysis, visualization, and management of large datasets collected from diverse sources, such as surveys, community-based data, and health records. This role involves collaboration with researchers, the data management team, and project coordinators to ensure efficient and accurate data processing and reporting.

Roles  Responsibilities:

Data Management:

• Support the development & management of integrated data management platforms i.e. REDCap.
• Designing digital tools for both desktop and handheld device interfaces using REDCap.
• Data entry and systematic archiving of all non-digital data collection tools.
• Ensure data integrity and security, following standard protocols.

Data Cleaning:

• Develop and maintain data using Python/R to clean and process large datasets.
• Identify and correct data quality issues, including outliers and missing values.

Data Analysis & Reporting:

• Conduct descriptive and inferential analysis of data.
• Prepare reports and summaries of analytical findings, both for academic publications and internal purposes.

Data Visualization:

• Create interactive data visualization dashboard using R (ggplot2, Shiny) or Python (matplotlib, seaborn, Plotly) or any other data visualization software.
• Utilize tools like QGIS to create maps for visualizing spatial data and geographic trends.
• Collaboration Communication:
• Coordinating with Field staff to collect data, provide timely feedback to data collectors for data discrepancies.
• Support training of field-level data collectors on the use of instruments and handheld devices.
• Work closely with researchers and project teams to understand data needs and requirements.
• Participate in team meetings and contribute to discussions on project progress and data-related challenges.

Documentation:

• Day-to-day data backups on servers or external hard disk.
• Maintain thorough documentation of data management and analysis processes.
• Any other activity as per the need of programme or tasks assigned by the supervisor.