Vasilii is a MSc Data Science for Politics & Policymaking student. As part of the Masters, he undertook a placement with Network Rail where he used data science methods to better understand rail demand.
Tell us about your journey to doing a Masters. What did you study at undergraduate level and where?
I completed a specialist degree in International Relations in my hometown of Vladivostok. After that, I worked on various projects as a PR manager, project manager, and press secretary.
While working with large quantities of online data for a social media analytics project, I realised the importance of big data in finding trends, predicting outcomes, and formulating policies and initiatives. It was then that I developed an interest in the intersection of data and policymaking, realising the immense potential for data-driven approaches in shaping effective policies.
What made you first apply for the Masters?
The MSc Data Science for Politics & Policymaking at the University of Strathclyde caught my attention due to its combination of data and social science modules. While I hadn't initially planned to pursue a career in data science, I was captivated by the potential of using data to gain deeper insights into the processes that shape our society and develop evidence-based policy solutions.
With modules from both the School of Government & Public Policy and the Department of Computer & Information Sciences, the course offered the perfect opportunity to combine my passion for policy research with my interest in data science.
How have you enjoyed the course so far?
I found the modules of the course to be intellectually stimulating, offering diverse approaches to data science. Each class had its own perspective and focus, making the learning experience engaging and thought-provoking.
The coursework was intensive, requiring a significant commitment of time and effort. However, it exposed us to a wide range of methodologies, tools, and real-world applications, preparing us for the complexities and demands of working in the field of data science.
One of the most insightful modules for me was Quantitative Methods: Survey Methods which introduced us to the statistical programming language R. Through this module, we gained an understanding of how to utilise R for survey data analysis and data visualisation. Another memorable class was Database Fundamentals, which introduced us to Structured Query Language (SQL) and taught us how to effectively manage and query data using SQL.
The course has helped me gain exposure to various real-world applications of data science, from simple data handling to building complex machine learning models. Studying at Strathclyde has affirmed my desire to utilise big data to make a positive impact in society and drive meaningful change.
What Data Science skills have you developed as part of the course?
As part of the course, I have gained basic proficiency in such programming languages as Python, R, and SQL which are essential for data manipulation and analysis. Additionally, I have learned statistical modelling techniques, machine learning algorithms, and data visualization methods. While it was challenging at times, I now feel more confident working with datasets and can apply data science methodologies to extract meaningful insights.
Tell us about your placement.
I was fortunate to secure a placement with Network Rail, the infrastructure manager of most of the railway network in Great Britain. The opportunity arose through the strong network and connections that the University of Strathclyde has with various organizations in Scotland and the United Kingdom.
I worked on analysing large-scale datasets related to patronage and rail demand. This experience not only allowed me to apply the data science skills I acquired during the course but also provided valuable insights into the practical challenges and opportunities in using data for policymaking.
What are your plans for after you graduate?
The course has helped me gain exposure to various real-world applications of data science, from simple data handling to building complex machine learning models. Through these projects, I have gained a better understanding of my capabilities and interests within the field of data science. Studying at Strathclyde has affirmed my desire to utilise big data to make a positive impact in society and drive meaningful change.
After I graduate, my plan is to pursue a career in data-driven policy analysis or consulting at a non-governmental organization or a think tank. The MSc Data Science for Politics & Policymaking has equipped me with knowledge in both data science and policy analysis. I believe that the MSc will help me become a competent professional and make a meaningful contribution to shaping evidence-based policies, addressing social problems, and managing projects focused on the future.