Summary
Date Posted: Wednesday, November 16, 2022 , Base Salary: Not Disclosed

JOB DETAILS:

Responsibilities
• Support the DMAC lead and Manager in the day to day administrative functions
• Provide technical contributions in a fast paced team environment to accelerate our efforts on building an analytics driven product pipeline
• Perform independent statistical analysis, computer programming, predictive modelling, and contribute to new studies
• Build cross-functional relationships to collaboratively partner with the other collaborators and effectively network within the Data Science community
• Use advanced mathematical models and machine learning to deliver insight, recommendations and solutions to different projects within UZIMA-DS project
• Contribute to the development of code, computational tools and databases for mining and visualizing large data sets resulting from maternal newborn and child health as well as mental health studies
• Develop sustainable, consumable, accurate and impactful reporting on model inputs and outputs
• Use the project data and resources to develop a PhD thesis and scientific papers leading to the award of the doctoral degree

Requirements
• Holder of Master’s Degree and currently pursuing a PhD in Computer Science, Statistics/Biostatistics, Mathematics or equivalent in a recognized university
• Proficiency using one or more programming or scripting languages such as Python, R, MATLAB, Perl, SAS or C#
• Skills in Artificial Intelligence/Machine Learning methods, data integration and mathematical modeling as well as proficiency in ETL tools
• Experience in data management in relational databases such as MySQL
• Experience in data analysis using STATA, R, or other statistical software
• Experience working with longitudinal studies, handling large data sets and cloud computing: GCP, MS Azure is desirable
• Experience in visualizing/presenting data for stakeholders and the use of relevant data visualization tools
• Experience with relevant technologies e.g. Tensor Flow, Apache Flume, machine learning libraries
• Relevant professional experience with applied data analytics and predictive modeling

Work Hours: 8

Job Experience: No Requirements

Level of Education: Associate Degree

Job application procedure
Application letter together with detailed Curriculum Vitae, names of three referees, should be sent to the Manager, Talent Acquisition, Aga Khan University, via the email: hr.universityke@aku.edu  by 30th November 2022.
Please quote the position title on the email subject. Only short-listed candidates will be contacted.


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