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Internships with Te Tāhū Hauora provide students with hands-on experience in health data

Health Quality Intelligence
07 September 2023

The Te Tāhū Hauora health quality intelligence (HQI) team has welcomed two data science students, Ranen Lourdes and Felix Ng, as interns to collaborate on a project aimed at enhancing the data-driven insights within the health care sector. Both students, currently in their third year at Te Herenga Waka–Victoria University of Wellington, will contribute their skills to the data team at Te Tāhū Hauora until October.

An image of Ranen and Felix standing in front of a forest backdrop.

Caption: (L-R) Ranen Lourdes and Felix Ng, interns with the health quality intelligence team at Te Tāhū Hauora

Ranen Lourdes is studying towards a bachelor of commerce in data science and information systems, whereas Felix Ng is enrolled in a bachelor of science and specialising in data science and computer science. Their joint project with HQI focuses on revamping the process of data creation for health measures within the health system quality dashboard. The project entails a transition from SAS coding to using SQL databases for coding purposes.

Reflecting on his internship experience, Ranen explains, ‘this internship has been great for me to apply what I’ve learned from uni to a practical setting, and I’ve been learning new things every day I come in, data science related or not.’

Felix Ng echoed Ranen's sentiments and highlighted his aspiration to merge his technical skills with his passion for health data. ‘I was drawn to Te Tāhū Hauora by the incredible opportunity offered to work with health data. My ultimate aim is to apply my expertise in machine learning to the field of genetics. This internship is a stepping stone in that direction, giving me valuable hands-on experience in working with health data and providing a unique intersection between my technical skills and my interests in health data.’

In their roles, Felix and Ranen are primarily responsible for writing SQL code to clean, format and organise health data for various metrics, contributing to the ongoing effort to enhance the quality and accessibility of health-related information.