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Data Science Research Associate at Kamuzu University of Health Sciences (KUHeS)

  • Full Time
  • Blantyre
  • Salary: 00

Kamuzu University of Health Sciences (KUHeS)


The Kamuzu University of Health Sciences (KUHeS) is a comprehensive health and allied  sciences higher learning institution established with the primary function of training health workers  and conduct health research. The Health Economics and Policy Unit (HEPU) is a unit under the  Department of Health Systems and Policy within the School of Global and Public Health  (SOGAPH) at KUHeS which was jointly established with Ministry of Health. With support from the  Health Services Joint Fund (HSJF), the Health Economics and Policy Unit (HEPU) has been  tasked with conducting health economics and policy analyses. The goal is to provide evidence for  policy initiatives that will improve the capacity to generate and use health economics evidence in  health sector decision-making. The HEPU aims to enhance the ability to make informed policy  decisions by applying economic principles to health issues. Through this initiative, the unit seeks  to strengthen the link between research evidence and policy formulation in the health sector. The  HEPU would therefore like to engage the following capacities to be part of their vibrant team of  researchers and policy analysts:

Data Science Research Associate  

Location: (to be indicated) 

Type: Full time

Duration: Two years, renewed yearly based on performance

The HEPU seeks to engage a Data Science Research Associate who will lead collection, analysis  and interpretation of large data to contribute to ongoing HEPU projects.

Job Summary 

The main purpose of this position is to contribute to research activities, develop data bases,  manage data and model systems for the different work streams assigned to HEPU by the Ministry  of Health.

Key Duties and Responsibilities  

The Data Analysis Research Associate will be expected to perform the following duties and  responsibilities:

✓ Data Collection: Gathering relevant data from various sources, which could include  databases, surveys, experiments, or other data repositories.

✓ Data Cleaning and Preparation: Processing raw data to identify and rectify errors,  missing values, or inconsistencies. This step is crucial for ensuring the accuracy and  reliability of the analysis.

✓ Statistical Analysis: Applying statistical methods and techniques to analyze data and  extract meaningful patterns, relationships, and trends. This could involve descriptive  statistics, regression analysis, hypothesis testing, or machine learning algorithms.

✓ Data Visualization: Creating visual representations of data such as charts, graphs, and  dashboards to effectively communicate findings and insights to stakeholders. ✓ Report Writing: Summarizing analysis results into clear and concise reports or  presentations. This may involve explaining methodologies, interpreting findings, and  making recommendations based on the data.

Required Qualification and Skills 

Candidates applying for this position must have the following:

✓ Bachelor’s degree in Health Systems, Data Science or related

✓ Advanced use of KOBO and excel to manage large survey data collection  ✓ Advanced use of excel programming to analyse policy questions

✓ Excellent data management skills using a variety of software preferable stata, SPSS and  other relevant software

Method Of Application

Interested candidates who meet the above requirements should send their applications including  cover letter, CV with names of three traceable professional referees and copies of relevant  certificates to:

The Registrar

Kamuzu University of Health Sciences

Mahatma Gandhi Road Campus

P/Bag 360


Blantyre 3

Or email to: [email protected] copy [email protected]

Indicate position title on the envelope for hard copy applications and indicate the same in the  subject line of your email for electronic submissions.

Applications should reach the Registrar not later than 10th June, 2024. Only short-listed  candidates will be acknowledged.

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