SGHI seeks a highly motivated Senior Associate – Data Integration/Analyst to join its Global Health Security (GHS) delivery team. The Senior Associate will design and implement the statistical and signal-generation methods used to detect and corroborate patterns, such as cross-program signals and disease clusters, working within a pre-agreed selection and evaluation framework. The Senior Associate will work closely with the Technical Lead, the Data Governance Lead, and the Informatics & Surveillance Lead to ensure that signals prepared for review by the Kenya National Public Health Institute (KNPHI) meet the project’s statistical, data-quality, and documentation standards.This role combines advanced statistical analysis, surveillance methods development, data-quality assurance, and rigorous documentation, and is designed for a self-driven professional with strong quantitative skills, sound judgment, and the ability to translate complex analysis into clear, decision-ready outputs for government and technical stakeholders

Key Responsibilities

• Analytical Method Development
  • Design and implement statistical and signal-generation methods for the project’s use cases, including cross-program patterns and disease clusters.
  • Apply pre-agreed statistical and data-quality thresholds, including adjustments for population and seasonal patterns, before any signal is submitted for review.
  • Test methods against routine comparators and document their performance, limitations, and confidence criteria.
• Signal Generation & Quality Assurance
  • Prepare signals for KNPHI review, specifying the location, period, syndrome, contributing sources, source quality, magnitude, confidence level, and material limitations of each signal.
  • Corroborate single-stream deviations across independent data sources before escalation, applying pre-specified thresholds.
  • Support the measurement of data-source latency, coding consistency, and amendment and rejection rates, and assess their effect on signals.
• Portability & Documentation
  • Document signal definitions, analytical logic, confidence criteria, and test cases so that a qualified third party can reproduce the methods.
  • Contribute to the technical annex describing the re-identification risk assessment and the analytical architecture.
  • Support the preparation of materials for the project’s mid-line review and evidence synthesis.
• Collaboration & Reporting
  • Work with the data engineering team on data quality, record-linkage performance, and denominator availability relevant to the analysis.
  • Report analytical progress, risks, and data limitations to the Technical Lead and the Informatics & Surveillance Lead.
  • Contribute to quarterly data-quality and progress reporting to the Gates Foundation and KNPHI.

Skills & Experience Required

• Bachelor’s degree in data science, Statistics, Epidemiology, Biostatistics, Computer Science, or a related field.
• Minimum of 5 years’ experience in data analysis or data science.
• Strong knowledge of statistical and epidemiological methods
• Strong quantitative and statistical analysis skills, with proficiency in a data-science programming language (e.g., Python or R) and SQL.
• Sound understanding of data privacy, pseudonymization, and role-based access principles applicable to the analysis of sensitive health data.
• Ability to translate complex analytical findings into clear, decision-ready outputs for non-technical stakeholders, such as county and KNPHI reviewers.
• Rigorous, detail-oriented approach to the testing, documentation, and reproducibility of analytical methods.
• Fluency in English (speaking, reading, and writing) and working proficiency in Kiswahili.

Preferred

• Master’s degree in data science, Statistics, Epidemiology, Biostatistics, Computer Science, or a related field.
• Experience in health or public health data analysis.
• Experience working with the Ministry of Health and county governments in Kenya.

Note: This job description outlines the main responsibilities of the role but is not exhaustive. The jobholder may be asked to perform other reasonable duties consistent with the role’s level and skills, as assigned by SGHI.

• Design and implement statistical and signal-generation methods for the project’s use cases, including cross-program patterns and disease clusters.
• Apply pre-agreed statistical and data-quality thresholds, including adjustments for population and seasonal patterns, before any signal is submitted for review.
• Test methods against routine comparators and document their performance, limitations, and confidence criteria.
• Prepare signals for KNPHI review, specifying the location, period, syndrome, contributing sources, source quality, magnitude, confidence level, and material limitations of each signal.
• Corroborate single-stream deviations across independent data sources before escalation, applying pre-specified thresholds.
• Support the measurement of data-source latency, coding consistency, and amendment and rejection rates, and assess their effect on signals.
• Document signal definitions, analytical logic, confidence criteria, and test cases so that a qualified third party can reproduce the methods.
• Contribute to the technical annex describing the re-identification risk assessment and the analytical architecture.
• Support the preparation of materials for the project’s mid-line review and evidence synthesis.
• Work with the data engineering team on data quality, record-linkage performance, and denominator availability relevant to the analysis.
• Report analytical progress, risks, and data limitations to the Technical Lead and the Informatics & Surveillance Lead.
• Contribute to quarterly data-quality and progress reporting to the Gates Foundation and KNPHI.

• Strong knowledge of statistical and epidemiological methods
• Strong quantitative and statistical analysis skills, with proficiency in a data-science programming language (e.g., Python or R) and SQL.
• Sound understanding of data privacy, pseudonymization, and role-based access principles applicable to the analysis of sensitive health data.
• Ability to translate complex analytical findings into clear, decision-ready outputs for non-technical stakeholders, such as county and KNPHI reviewers.
• Rigorous, detail-oriented approach to the testing, documentation, and reproducibility of analytical methods.
• Fluency in English (speaking, reading, and writing) and working proficiency in Kiswahili.

• Bachelor’s degree in data science, Statistics, Epidemiology, Biostatistics, Computer Science, or a related field.
• Master’s degree in data science, Statistics, Epidemiology, Biostatistics, Computer Science, or a related field.
• Experience in health or public health data analysis.
• Experience working with the Ministry of Health and county governments in Kenya.