A political science graduate moving into a Data Analyst role at a leading tech company, these two things sound completely unrelated. Many people get stuck in the mindset that if they didn't graduate with a computer science degree or a related technical major, they have no chance of entering this field. But I want to tell you that this simply isn't true. My name is Karn, and I'm currently a Junior Data Analyst on the Data & AI team. And yes, I graduated from the Faculty of Political Science at Chulalongkorn University.
This is the story of my Data Analyst career change, starting from my internship to becoming a full-time employee at Seven Peaks Software.
Many people have an application or a product that inspires them, but my starting point was much simpler. It began when the system randomly recommended a Reddit thread about data analytics to me. That spark made me seriously interested in the field. I started researching and tried to build my very first project.
When I started actively finding a Data Analyst job around September 2024, the Thai tech job market was fiercely competitive. It felt like a small war, with everyone trying to break into the industry, and I was one of them.
I saw that Seven Peaks, which has a reputation as one of the best digital transformation consultancy firms in Thailand, was hiring a Data Analyst intern. I decided to apply even though I saw over 50 people had already applied on LinkedIn. To my surprise, I received a call for an interview. Soon after, I became a part of the team, and today, I've been here for almost a year as a full-time employee.
Once I started working, I learned one truth about this job. Most people mistakenly believe that a Data Analyst always works with perfectly cleaned and transformed data that has almost no errors. But in a real-world production environment, it's not like that at all.
My main responsibilities involve maintaining the company's internal data, from sourcing new updates to fixing bugs in the data pipeline. When I first started, I handled general administration, setting up Power BI, managing data mappings between Excel with Power BI, and creating prototypes for various ideas.
As I gained more experience with data, cloud services, and programming, I was assigned more complex projects that required specialized knowledge.
If you ask what tools I use daily to turn messy raw data into real-time dashboards that executives use for decision-making, the core tools can be divided into parts. The heart of it all is SQL and Python. I use these two to solve daily bugs.
Then there are the visualization tools. Power BI is the main stack we use to build internal dashboards. Most of the data is cleaned and transformed using Python and SQL before being reported in Power BI.
Besides these main tools, I also need to use Bash Scripting and Docker. I use them especially when deploying work after testing and moving it to the actual production environment.
Since I didn't come from a relevant major, on-the-job training was the most important thing for me. I remember one project for a global client in the food industry, a field where I had no prior experience. I learned and built all the unique expertise right here, but what truly helped me grow fast wasn't just the work itself. It was the team culture.
What truly impressed me was the lack of pressure. When we have sessions to learn something new, it doesn't feel like listening to a lecture. It’s an atmosphere of discussion, where we share what we know at that moment to help find the best solution together. The fact that the seniors took time out of their busy schedules to help me, combined with this open culture, gave me opportunities and trust. The trust was demonstrated when I was tasked with independently overseeing internal BI and AI projects, from design and building to bug fixing and presenting my own ideas.
Going from a political science intern to owning an internal AI project in less than a year is a very substantiated path of growth that I've experienced here.
This is the question I hear often, especially since I graduated from Political Science. For anyone interested but hesitant because they didn't graduate with a relevant degree, I can confirm that you can definitely start. Based on my trial-and-error experience, this is the most straightforward guide I have for those who want to make a Data Analyst career change.
If you ask what to start with, I recommend beginning with these three or four essential tools:
The next question is where should you study? And are certifications necessary?
My story proves that being a Data Analyst isn't defined by your academic background. This field is open to anyone with dedication, a genuine curiosity for new knowledge, and a strong collaborative attitude.
If you are someone passionate about solving problems, love analyzing data to find insights, and are looking for an organization willing to invest in your growth and trust your capabilities, a Data Analyst career change might be the right answer for you.
We are looking for people with a deep passion for transforming messy data into powerful insights that drive business. Ready to join us? View open positions on our Data & AI team and other roles here.
Karn applies a political science background and structural analysis to find key connections and insights hidden in data. He currently manages Seven Peaks’ internal data and helps develop complex client data pipelines, transforming raw data into powerful insights.
Karn started his tech journey as an intern before proving himself and growing into a full-fledged Junior Data Analyst. He is skilled in SQL, Python, and Power BI. He is deeply passionate about self-learning and tackling challenging problems.