November 19, 2024, by bbztlg

Gaining new experiences through a placement in health and wellbeing

Postgraduate student Hongwei Liang shares her experiences as a health and wellbeing data analyst during her placement, highlighting the key insights and lessons she gained along the way.

During my MSc data science course at the University of Nottingham, thanks to the recommendation of Beth Litchfield from the Careers and Employability Service, I had the invaluable opportunity to work as a Health and Wellbeing Data Analyst for What Have We Learnt Ltd. This placement, coordinated by the Researcher Academy Placements and Mobility team, particularly Gerry, who ensured a smooth interview and onboarding process, was an eye-opening experience that shaped my perspective on data science applications in the health sector.

Why I applied for the placement

The role immediately caught my attention because it combined two of my key interests: data science and health. I was drawn to the vision behind ‘Livedinsights’, an innovative platform founded by Charlie Wardle, who is doing something truly remarkable—his platform encourages people to share their lived experiences related to various health challenges such as cancer, anxiety, and so on. This kind of open, supportive environment fosters mutual encouragement and learning.

The opportunity to work on this platform, which aimed to promote health and wellbeing discussions, was deeply motivating. I wanted to contribute to this project by using data analysis to generate insights that could influence health conversations and support people facing similar challenges. However, I knew that the role also required stepping out of my comfort zo – particularly into the realm of marketing and public engagement, which was new to me.

My role and responsibilities

Working directly with Charlie Wardle, my primary responsibility was to analyse data collected from questionnaires on the platform. The aim was to generate actionable insights that could be used to promote ‘Livedinsights’ and encourage more people to contribute their experiences. This included developing promotional content based on the analysed data to raise awareness about the platform’s mission.

While the data analysis was familiar territory for me, delving into marketing and promotion was a new and initially intimidating challenge. I collaborated with my colleague, Vedashree, to strategize how we could engage different communities and organizations. Together, we participated in events and promoted the platform to encourage more participation.

Personal growth and reflections

Throughout the placement, I honed my data analysis skills, especially in working with real-world data tied to sensitive health topics. And I also grew in confidence—working in a professional environment where English isn’t my first language was initially daunting, but by the end, I felt empowered by the progress I had made.

This placement experience has had a profound impact on my personal and professional development. Not only did it strengthen my passion for health data analysis, but it also expanded my career horizons. I now feel more confident about potentially working in international environments in the future, and I’ve realized the significant role data can play in promoting health and wellbeing.

A highlight of my placement was when Charlie praised my work after I created a data-driven promotional poster. Knowing that my contribution was recognised and valued gave me a sense of accomplishment and reinforced my desire to continue working in this field.

Advice for future researchers

For anyone considering a placement, especially international students, I highly recommend taking the leap. It’s more than just a way to gain industry experience – it’s an opportunity to grow, adapt, and build confidence. The most important preparation is crafting a strong CV and cover letter, but equally important is having the courage to push yourself beyond your comfort zone. Placements like this offer invaluable professional growth and the chance to contribute to impactful projects.

Written by Hongwei Liang, MSc Data Science student

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