Quantitative/Qualitative Data Analyst (Temporary)

JOB DESCRIPTION 

Job Information

Title	Quantitative/Qualitative Data Analyst (Temporary)
Department	MERIIT
Duty Station	Neno District
Reports to	Research Officer
Second Line Reporting	Research and Impact Manager
Commitment	Full-time
Working Hours	40 hours per week

 Job Summary:

The Quantitative/Qualitative Data Analyst will play a
pivotal role in supporting research, program evaluation, and evidence
generation activities within
Partners In Health/Abwenzi Pa Za Umoyo (PIH/APZU).
The incumbent will be responsible for managing, analyzing, interpreting, and
presenting both quantitative and qualitative data to inform research findings,
programmatic decision-making, policy development and quality improvement
initiatives.

Working closely with the Principal Investigator, Research
Officer, program teams, and external collaborators, the Data Analyst will
support the implementation of research protocols, ensure high-quality data
analysis, and contribute to the generation of evidence that strengthens health
systems and improves patient outcomes. The role requires expertise in
statistical and thematic analysis, data visualization, report writing, and
interpretation of findings within public health and social science contexts.

The incumbent will contribute to the development of research
outputs, including reports, presentations, manuscripts, conference abstracts,
and policy briefs, while ensuring adherence to ethical standards, research
protocols, and organizational priorities.

3.0 Core Responsibilities

3.1 Quantitative Data Analysis

• Conduct
  statistical analysis of research, programmatic, and survey datasets in
  accordance with approved study protocols and analysis plans.
• Perform
  data cleaning, validation, management, and quality assurance to ensure
  accuracy, consistency, and completeness of datasets.
• Analyze
  retrospective and prospective datasets using appropriate statistical
  methods and analytical techniques.
• Generate
  descriptive, inferential, and advanced statistical analyses to address
  research questions and study objectives.
• Develop
  statistical models and conduct trend analyses, regression analyses, and
  other analytical approaches as required.
• Support
  database management and preparation of datasets for analysis and
  reporting.
• Interpret
  analytical findings and provide evidence-based recommendations to support
  program implementation and decision-making.

3.2 Qualitative Data Analysis

• Conduct
  thematic analysis of qualitative data obtained through interviews, focus
  group discussions, observations, and other research methodologies.
• Transcribe,
  review, code, organize, and analyze qualitative datasets using approved
  analytical frameworks.
• Utilize
  qualitative data analysis software such as NVivo, Dedoose, or
  similar platforms to facilitate systematic analysis.
• Identify
  emerging themes, patterns, barriers, facilitators, and key findings
  relevant to study objectives.
• Synthesize
  qualitative findings and integrate them with quantitative results to
  support mixed-methods research approaches.
• Ensure
  qualitative analysis maintains methodological rigor and accurately
  reflects participant experiences and perspectives.

3.3 Research Implementation and Technical Support

• Collaborate
  with Principal Investigators, Research Officers, and study teams
  throughout the research lifecycle.
• Support
  the development and implementation of data analysis plans, research
  protocols, and study tools.
• Participate
  in study design discussions and contribute technical recommendations on
  data management and analytical approaches.
• Provide
  technical support during data collection, data verification, and data
  quality improvement activities.
• Ensure
  compliance with research ethics requirements, data protection standards,
  and organizational policies.
• ▪ Support
  preparation of datasets and documentation for external reviews, audits,
  and dissemination activities.

3.4 Reporting, Dissemination, and Knowledge
Management

• Prepare
  comprehensive analytical reports, summaries, presentations, and dashboards
  based on study findings.
• Support
  the development of manuscripts, abstracts, conference presentations,
  policy briefs, and technical reports.
• Present
  findings to internal and external stakeholders in a clear and meaningful
  manner.
• Collaborate
  with research and program teams to translate data into actionable
  recommendations for policy and practice.
• Support
  organizational learning through dissemination of research findings and best
  practices.
• Maintain
  organized and secure analytical files, datasets, coding outputs, and study
  documentation.

3.5 Stakeholder Engagement and Collaboration

• Work
  closely with multidisciplinary teams, including clinical, programmatic,
  monitoring and evaluation, and research staff.

• Collaborate
  with academic institutions, government stakeholders, implementation
  partners, and donors as required.
• Participate
  in research meetings, technical working groups, data review sessions, and
  dissemination events.
• Foster
  collaborative relationships that support evidence generation and
  utilization across PIH/APZU programs.
• Contribute
  to strengthening a culture of data use and evidence-based decision-making
  within the organization.

3.6 Capacity Building and Professional Development

• Provide
  mentorship and technical support to research assistants, data collectors,
  and junior research staff on data analysis methodologies.
• Support
  training initiatives related to quantitative and qualitative research
  methods, data management, and analytical software.
• Stay
  informed about current developments in public health research,
  epidemiology, biostatistics, and qualitative methodologies.
• Participate
  in continuous professional development opportunities and contribute to
  strengthening analytical capacity within the Research Department.
• Perform
  any other duties assigned within the Research Department from time to
  time.

4.0 Expected Competencies, Attributes, and Behaviors

4.1 Core Competencies

• Quantitative
  Analysis and Biostatistics: Demonstrated expertise in statistical
  analysis, data interpretation, and management of complex datasets.
• Qualitative
  Research and Analysis: Strong knowledge of thematic analysis, coding
  frameworks, qualitative methodologies, and mixed-methods research.
• Research
  Methodology: Solid understanding of epidemiological methods, study
  design, implementation science, and health systems research.
• Data
  Management and Quality Assurance: Ability to maintain high-quality
  datasets through rigorous cleaning, validation, and quality control
  processes.
• Scientific
  Writing and Dissemination: Ability to develop high-quality reports,
  manuscripts, presentations, and knowledge products for diverse audiences.

4.2 Behavioral Attributes

• Analytical
  Thinking: Demonstrates strong critical thinking and problem-solving
  skills when interpreting complex datasets and research findings.
• Attention
  to Detail: Maintains high levels of accuracy, consistency, and
  quality in all analytical tasks.
• Integrity
  and Confidentiality: Adheres to ethical principles and maintains
  confidentiality of research participants and organizational data.
• Collaboration
  and Teamwork: Works effectively with multidisciplinary and
  multicultural teams across different levels of the organization.
• Adaptability
  and Innovation: Demonstrates flexibility and openness to innovative
  approaches in research and data analysis.
• Results-Oriented
  Approach: Focuses on delivering high-quality outputs within
  established timelines while maintaining methodological rigor.

4.3 Technical Competencies

• Statistical
  Software Proficiency: Advanced knowledge of SPSS, STATA, R, Python,
  or other statistical analysis software.
• Qualitative
  Analysis Software: Experience
  using NVivo, Dedoose, Atlas.ti, or related qualitative data
  analysis platforms.
• Data
  Visualization: Ability to develop meaningful visualizations,
  dashboards, and presentations that effectively communicate findings.
• Database
  and Data Systems Knowledge: Familiarity with electronic data
  collection and management systems including CommCare, ODK, REDCap, SurveyCTO, OpenMRS,
  or similar platforms.
• Communication
  and Presentation Skills: Ability to communicate complex analytical
  findings to both technical and non-technical audiences.

5.0 Qualifications and Experience

• Bachelor’s Degree
  in Statistics, Public Health, Epidemiology, Computer Science, Social
  Sciences, Mathematics, Biostatistics, Data Science, or a related field.
• Minimum
  of two (2) years of experience in quantitative and/or qualitative data
  analysis, preferably in public health, research, development, or social
  science settings.
• Demonstrated
  experience conducting quantitative data analysis using SPSS, STATA, R,
  Python, or related software.
• Demonstrated
  experience conducting qualitative analysis
  using NVivo, Dedoose, Atlas.ti, or similar software
  packages.
• Strong
  understanding of statistical methods, research methodologies, and data
  management principles.
• Experience
  working with electronic data collection tools such
  as CommCare, REDCap, SurveyCTO, ODK, KoboToolbox, or
  related platforms.
• Proven
  ability to prepare technical reports, presentations, manuscripts, and
  research dissemination products.
• Experience
  supporting public health, implementation science, operational research, or
  health systems research studies will be an added advantage.
• Demonstrated
  ability to manage large datasets while maintaining high standards of data
  quality and integrity.

6.0 Additional Notes

• Willingness
  to work in rural and resource-constrained settings.
• Ability
  to manage multiple analytical assignments simultaneously while meeting
  project deadlines.
• Commitment
  to evidence-based practice, health equity, social justice, and
  strengthening health systems.
• Strong
  interest in public health research, implementation science, and
  policy-relevant evidence generation.
• Opportunity
  to contribute to impactful research that informs healthcare delivery,
  policy development, and improved health outcomes in Malawi and beyond.

7.0 Method of application

All interested and qualified candidates based in
Malawi should apply strictly through https://www.pih.org/employment on
or before 13^th September 2026. Only shortlisted candidates will
be invited for interviews.

8.0 Safeguarding Commitment

Partners In Health/Abwenzi Pa Za Umoyo (PIH/APZU)
is committed to safeguarding staff, children and communities with whom we work
from sexual exploitation, abuse and sexual harassment. Therefore, any offer of
employment is conditional upon the successful completion of applicable
background checks.

The Organisation does not charge any fees at any stage
of the recruitment process. If you are asked to make a payment at any
stage of the recruitment process, please contact us through our toll-free
line:  0884502020.