Nino is a graduate from the MSc Data Science for Politics & Policymaking within Strathclyde's Department of Government & Public Policy

Tell us a little about your background...

I originally come from Georgia, where I worked for several years at the Ministry of Defence, leading organisational development and internatioanl research projects focused on ethics, human rights, gender equality, and institutional reform. Alongside policy work, I was deeply involved in research design, data collection, and analysis, which gradually strengthened my interest in evidence-based policymaking.

After several years in public sector roles, I decided to deepen my technical skills and pursue an MSc in Data Science for Politics and Policymaking at the University of Strathclyde. I graduated with Distinction and currently work as a Research Assistant at Strathclyde, supporting large, multi-country research project involving complex datasets.

What drew you towards undertaking this degree? And what appealed to you about Strathclyde in particular?

My professional background was strongly rooted in public policy and governance, but I wanted to strengthen my quantitative and computational skills to become more confident in advanced data analysis. I was particularly interested in bridging political science with modern data science tools such as R, machine learning, and big data analytics. What appealed to me most was that each completely new subject  including R, machine learning, big data, and database fundamentals  was supported by practical lab sessions. This made the learning process much more accessible, especially for students who had never previously encountered technical terminology or programming concepts.

Tell us about the format of the programme...

The programme is intensive but very well structured. A typical week included lectures, hands-on lab sessions in R and Python, seminars on research design and methodology, and independent project work, particularly towards the end of the year.

There was a strong practical component : we were constantly working with real datasets, and the course included both group and individual assignments. It was academically demanding, but in a very rewarding way, as it continuously pushed us to apply what we were learning in real-world contexts.

The dissertation phase was particularly meaningful for me, as it allowed me to combine theory with advanced statistical modelling on a topic I care deeply about - democratic backsliding and public trust in government. During this process, my supervisor introduced me to Structural Equation Modelling (SEM), which was a transformative learning experience and significantly expanded my understanding of complex quantitative analysis.

Tell us about your experience on placement...

Although I do not undertake a formal placement, by the end of the second semester I begin working as a Research Assistant on a university research project. In this role, I work with large multi-country datasets, focusing on data cleaning, validation, and the development of reproducible R scripts to ensure accuracy and transparency in the analysis. I also prepare detailed methodological notes and documentation to support transparent research processes and maintain high data quality standards across projects. This experience is particularly valuable because it allows me to directly apply the knowledge and skills I develop during the programme in a real research environment. My supervisors are extremely supportive and provide continuous guidance, which helps me strengthen both my technical skills and my confidence as a researcher. It genuinely feels like a transition from learning theory to applying data science in practice.

What is the academic support at Strathclyde like?

The academic support at Strathclyde is genuinely strong. Lecturers are approachable, responsive, and invested in students’ development. The small cohort size made it easy to ask questions and receive detailed feedback.

What are the facilities at Strathclyde like?

Strathclyde offers excellent facilities. The Andersonian Library provides quiet study areas as well as collaborative spaces, which were very helpful during project work. Computer labs are well-equipped for data-intensive tasks, and software access is strong.

The campus itself is modern and centrally located in Glasgow, which makes student life convenient and vibrant. It creates a professional but welcoming academic environment.

Where are you working now...

I currently work at the University as a Research Assistant and am also involved in a short-term project (outside the uni) as a Data Scientist and Senior Project Manager. In these roles, I work with complex datasets, develop analytical workflows, and contribute to research outputs that inform policy discussions.

Looking ahead, I aim to continue working at the intersection of data science, governance, and public policy.

What advice would you give to someone considering applying for this course?

I would strongly recommend being curious, open to learning, and ready to work consistently. The programme is demanding, especially if you are new to programming or statistics, but it is extremely rewarding.

Do not be afraid if you come from a non-technical background - many of us did. What matters most is commitment and willingness to practice.