Pros
It is difficult to identify many positives from my overall experience. However, there was one project where I worked with a strong team and a genuinely positive culture. The work was engaging, collaborative, and development-focused. On that project, I felt challenged in a productive way and was able to build meaningful skills. It demonstrated that with the right leadership and environment, the experience could be rewarding.
Cons
My experience within the Analytics & AI function did not provide the technical growth I had expected. As a graduate, I joined with the intention of developing my data analytics and AI capabilities, but I did not receive structured training or meaningful hands-on exposure to build those skills. The first time I encountered practical SQL content was through a basic internal slide deck, rather than through guided project experience or formal development. Role clarity was also a significant issue. I was staffed as a Data Analytics and Reporting Lead, but the responsibilities did not reflect that title. The role largely became reactive client support work, often involving late evenings responding to ad-hoc requests. When concerns were raised with project leadership, they were not initially handled constructively, which led to escalation through internal channels. While HR was supportive, the situation highlighted inconsistencies in how wellbeing and role expectations were managed. Recognition and progression processes felt misaligned. Despite strong performance feedback on projects and consistent delivery, visibility appeared to carry more weight than output. Those who were more vocal or heavily involved in internal initiatives seemed to gain greater recognition, regardless of project performance. As a result, I often felt undervalued despite working hard and receiving positive project-level feedback. There also appears to be a disconnect between project contribution and promotion criteria. Individuals are primarily assessed on billable project performance day-to-day, yet advancement depends significantly on internal contributions. This created pressure to engage in internal work largely to satisfy promotion requirements, rather than because it added meaningful value. Finally, professional development within the function felt overly dependent on informal, on-the-job learning. In a specialist area such as Analytics & AI, a clearer development pathway with structured technical training would significantly improve the experience for graduates and early-career professionals.