Back in late 2011, fresh out of university and eager to kickstart my career, I joined the British Transport Police (BTP) through a recruitment agency as a Filing Clerk in Birmingham. It was a humble beginning, but one that laid the groundwork for my professional journey. Soon after, I transitioned to the role of HR Service Desk Officer before moving into a position as an HR Data Analyst—a role I held for several years.
As an HR Data Analyst, I began to develop the foundational skills I use today. These skills were built through a combination of exposure to real-world challenges, the necessity of problem-solving, and a willingness to experiment and learn through trial and error. After that, I spent a couple of years as a Workforce Planning Advisor. Across these roles, I gained invaluable experience and insights that shaped my career path. Along the way, I also completed some Project Management courses, which broadened my skill set, even though I ultimately decided that route wasn’t for me.
While some people have a clear life plan or a specific job in mind, that wasn’t the case for me. My approach has been to embrace opportunities that align with my interests, and I’ve been fortunate to have the support of BTP in exploring roles that challenged and engaged me.
A Pivot Toward Data Science
In early 2019, I noticed an exciting opportunity advertised through BTP’s apprenticeship program. Although I didn’t have a definitive career plan, I knew I enjoyed the analytical and technical work I’d been doing. In Autumn 2019, I began a degree apprenticeship in Data Science. While the program started with in-person learning, the pandemic quickly shifted everything online, presenting its own unique set of challenges.
During the apprenticeship, I successfully applied for the role of Assistant Data Scientist and transitioned from the People & Culture team to the Analytics & Insight (A&I) team after spending eight years in my previous department. Both of my managers during this period were incredibly supportive of my studies, ensuring I had the required 20% of work time allocated for learning.
After completing my degree apprenticeship, I was thrilled to secure a Data Scientist role within BTP. If you’re considering an apprenticeship, I highly recommend it—it’s an excellent way to gain structured learning while building practical skills. However, be prepared to invest extra time outside the allocated work hours, as evenings and weekends often become essential for catching up on studies.
But what is Data Science?
Data Science is a multidisciplinary field that blends technical, mathematical, and business skills. It involves using tools like Excel and PowerBI, coding in languages such as Python, applying machine learning techniques, and translating insights into actionable narratives. At its core, Data Science is about solving problems and creating value.
At BTP, the work is varied. One day, we might be developing a dashboard; another day, we might be automating data processes, creating forecasts, or conducting detailed analysis to address specific questions. While there are some routine tasks, much of the work is project-based, requiring flexibility and the ability to juggle multiple priorities.
Here’s an example of a project I’ve worked on: managing access permissions for dashboards. Permissions are based on criteria like rank, job title, or team affiliation, and there are about 26 different permission groups. Every month, I run a script that checks all 5,000 BTP employees against these groups, determining who needs to be added or removed. The process involves around 130,000 checks and takes less than a minute to execute—a testament to the power of coding and automation.
Would you like to know more?
If you’re interested in developing your skills in the areas of data science or data analysis; getting better with Excel/PowerBI, either for personal knowledge or even to help with a career change and asked what I could suggest, I would offer up the following:
- YouTube – there are plenty of good tutorials that people have uploaded, all the way from beginner to advanced.
- Get a dataset and have a play – take a copy of a dataset and just mess around with it. Think of a scenario and try to create charts or do some analysis. If you’re stuck, turn to online resources to help and if all goes horribly wrong then start again.
- Khan Academy or Udemy – these are paid for services, often with discounts so keep an eye-out, that are defined course. May help if you want structure to your learning.
- Connect – reach out to people.
- Consider an apprenticeship – there a variety of levels to suit your requirements, but just remember what I said about evening and weekends!
