Move Thesis Project Intern (Estágio Curricular)

The Patient Global Impression of Change (PGIC) is a critical metric for evaluating perceived improvement in patients’ health and well-being during treatment. This thesis aims to optimise PGIC outcomes by leveraging advanced data analysis and predictive modelling techniques to identify and address key drivers of change. The project will focus on understanding the interplay between various factors, such as communication triggers, frequency and content of interactions, member behaviours, and the type and frequency of prescribed workouts. By extracting actionable insights from these variables, the study seeks to optimise internal operations resulting in an enhanced patient experience and perceived value.

The project will include the development of a computational solution from scratch, such as a predictive time-series model, capable of identifying at-risk members and enabling active outreach to support their progress. This solution will build upon existing codebases and a substantial Sword proprietary dataset and will involve extending Sword’s capabilities to address the unique challenges posed by real-world healthcare applications. Technologies such as Phoenix and natural language processing (NLP) will play a pivotal role in analysing communication patterns, tailoring outreach strategies, and improving patient engagement.

The thesis will contribute to both the academic research field and commercial applications by offering data-driven insights and scalable solutions for optimising PGIC. Through a creative and critical application of advanced techniques, the study will address open-ended and challenging problems in healthcare analytics. Additionally, the findings will be effectively communicated through detailed reports and defended under rigorous scrutiny, ensuring both transparency and scientific rigor.

Ultimately, this research will lay the foundation for improved patient engagement and care outcomes, while pushing the boundaries of computational solutions in healthcare analytics. The developed methodologies will have broader implications for enhancing patient-centred care strategies in various clinical and wellness settings.

What you need to have:

• Currently enrolled in or recently graduated from a Bachelor’s or Master’s program in Engineering, Computational or Data Science, Data Analytics or a related field.
• Availability to participate in a curricular or extracurricular internship.
• Ability to develop a computational solution from scratch, substantially extend the capabilities of an existing code, or build a model to analyse and interpret a substantial dataset.
• Creatively and critically employ techniques to solve open-ended, real-world, challenging problems.
• Ability to effectively communicate your work by writing reports and defending it under critical questioning.
• Strong analytical skills and proficiency in data visualisation tools such as Excel, Looker or similar tools.
• Detail-oriented, organised and capable of managing multiple tasks simultaneously.
• Excellent communication skills in both Portuguese and English, with a collaborative and proactive mindset.