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Job Description

Field Data Supervisor, LOSHAK, Population Health - (260001PD)

Field Data Supervisor

Department: Population Health

Division: Medical College

Location: Nairobi, Kenya

Project Overview

The Longitudinal Study of Health and Ageing in Kenya (LOSHAK) is a major research collaboration between the Aga Khan University in Nairobi and the University of Michigan, involving multiple Kenyan and international partners including Kenya's Ministry of Health and Kenya National Bureau of Statistics. Funded by the U.S. National Institute on Health, this project will collect multi-modal data (surveys, biological measures, mobile health assessments, etc.) from 8,955 older Kenyans, examining nearly all aspects of their physical, cognitive, psychosocial, and economic well-being.

Role Summary

The LOSHAK Field Data Supervisor will support electronic data collection and device-based measurements. The position is responsible for managing CAPI systems, field tablets, paradata monitoring, bio sample data workflows, and device-based data collection including UPAS V2+ air quality monitoring devices and Actigraph devices. The role ensures that field data systems and monitoring devices are properly deployed, maintained, and integrated with survey workflows while supporting real-time monitoring of data completeness, quality, in compliance to the study protocol and Kenya Data Protection Act, 2019.

Key Responsibilities

Capi system management

In collaboration with the Data Manager, configure and maintain electronic data collection platforms (Survey CTO/ODK/REDCap / Blaise); deploy instruments to devices (tablets and /or laptops); and manage questionnaire version control.

Tablet and field equipment management

• Prepare, distribute and maintain devices (laptops and or tablets) and accessories; troubleshoot hardware/software issues; maintain equipment inventory and asset tracking.
• Device-based data collection support
• Support deployment and monitoring of UPAS V2+ air quality monitoring devices and Actigraph devices; ensure proper installation, calibration and retrieval according to protocol.

Data synchronization and management

• Monitor daily synchronization of survey and device data; ensure secure transfer to central servers; resolve upload errors.

Paradata monitoring and field data quality

• Monitor timestamps, GPS coordinates, interview duration and submission patterns; generate data quality reports and flag protocol deviations that shall be resolved by the relevant data and technology infrastructure technical working group

Bio-marker sampling support

• Support the collection process of dried blood spots (DBS) and physiological measures (anthropometry, blood pressure, pulse rate, grip strength) by ensuring proper device functionality and data recording, unique bar code identification and labelling are captured

Informed consent process support

• Assist in ensuring complete and proper administration of informed consent for all stages of data collection.

Data cleaning and validation support

• Assist the Data Manager in implementing pre-programmed filters and validation rules in electronic forms; contribute to real-time data checking and error reporting.

Technical support to field teams

• Provide technical assistance to enumerators on tablets, CAPI tools and monitoring devices; troubleshoot issues during fieldwork.

Training and capacity building

• Support training of enumerators and supervisors on electronic data collection systems, device deployment and handling and data quality procedures.

Documentation and reporting

• Maintain documentation of device deployment, system configuration and data quality checks; report technical issues to supervisors.

Required Qualifications

• Bachelor’s degree in statistics, data science, public health computer science, information systems, or a related field.

Relevant Experience

• At least 3 years of experience supporting electronic data collection systems for field research.
• Experience in training field staff on data collection tools and protocols.
• Experience with CAPI platforms such as ODK, SurveyCTO, REDCap or CSPro.
• Experience managing laptops, tablets and digital field equipment.
• Familiarity with environmental monitoring and wearable devices is an advantage.
• Experience working in LMICs context and research and academia fields.
• Knowledge and experience in data management and quality control procedures in large-scale health or social science studies.
• Familiarity with ethical considerations and informed consent processes in research.
• Experience with data security and confidentiality protocols.

Personal Characteristics & Behaviours

• Strong problem-solving skills, analytical and attention to detail
• Ability to provide technical support and training to field teams
• Strong communication and teamwork skills.
• Proactive in identifying and addressing potential data quality issues.
• Adaptability and flexibility to respond to unforeseen challenges during fieldwork.
• Cultural sensitivity and ability to interact effectively with diverse community members.

Primary Location

: Kenya

Organisation

: Aga Khan University Hospital Kenya

Employee Status

: Regular

Job Type

: Standard

Job Posting

: 29/04/2026, 9:00:58 AM

Closing Date

: 14/05/2026, 6:59:00 PM