Maria: My Data Analyst Career

Hi Maria, thank you so much for taking the time, please introduce yourself to our site’s readers.

Hi, I’m Maria Balzan, a Senior Technical Data Analyst at Gamdom. I’m a free-spirited, adventurous thinker who enjoys diving headfirst into challenges—whether in data or in life. My role involves turning complex data into clear, actionable insights, working closely with management and teams such as finance and marketing to set KPIs and uncover meaningful trends.

I work remotely, with my two cats, Timmy and Kitty, keeping me entertained during breaks (and occasionally disrupting my meetings 😅). Outside of work, I’m always up for exploring new places and new ideas—anything that pushes me out of my comfort zone and keeps life interesting.

Can you share with us how you entered the data analytics industry, and tell us about your first data analyst role?

My journey into data analytics wasn’t entirely traditional, but it’s one I’m proud of. I’ve always had a love for numbers and problem-solving—teachers noticed it early on—but I wasn’t always sure how to channel that into a career. Like many people, I went through a phase of figuring out what I really wanted to do.

Eventually, I decided to pursue a degree in Mathematics, Statistics, and Operations Research. It was very challenging but rewarding, and it gave me the foundation I needed. During my third year, Betsson offered 4 data analyst internship roles to my class. It was competitive, but I was one of the selected, which was a turning point for me. That first experience taught me that succeeding in analytics isn’t just about technical skills or high grades; it’s also about asking the right questions, understanding the business, and being willing to step out of your comfort zone to learn.

What is it that you're personally finding most exciting about working in analytics?

What excites me most about working in analytics is how every day feels different. It’s like piecing together a puzzle where the picture constantly changes, but the satisfaction of finding the connections never fades. Working in a smaller company like Gamdom means I get to be involved in all kinds of projects, from building datasets, designing reports to setting KPIs, building dashboards, and investigating trends that lead to impactful decisions.

But what really keeps me going is seeing the tangible results of my work. For example, helping a team move from data-blind to data-driven and watching that shift lead to real business growth is incredibly rewarding. I also love that analytics combines creativity, problem-solving, and storytelling—you’re not just crunching numbers; you’re shaping a narrative that helps people make smarter decisions.

You seem to have had a very diverse experience, tell us more about working on projects across different industries (gaming industry, consulting and now financial). Could you tell us a bit more about those experiences, and share how what you do drives insights and business decisions?

My experience across the gaming and trading industries has shown me that while the surface details may differ, the underlying principles are remarkably similar. Both rely heavily on analyzing user behavior, understanding patterns, and balancing risk and reward. For example, in gaming, I’ve worked closely with finance, marketing, and CRM teams to analyze player behavior, optimize campaigns, and enhance customer retention. Similarly, in trading, the focus is on understanding trader actions, market dynamics, and optimizing strategies to manage risk and improve performance.

Although I haven’t worked formally as a consultant, I’ve developed a mindset that aligns with one. I approach problems by considering the bigger picture—what the business needs, where the opportunities are, and how data can provide actionable solutions. This perspective has helped me guide stakeholders toward decisions that make a real impact.

Both industries are data-driven and fast-paced, generating large volumes of data in real time. This requires not only technical expertise to process the data but also the ability to interpret and act on it quickly. For instance, in gaming, understanding when and how to tailor bonuses or promotions can significantly improve engagement and revenue. In trading, analyzing patterns in risk appetite or trading behavior can help shape financial products or strategies.

What drives me in both contexts is connecting the dots between data and actionable decisions. Whether it’s setting KPIs with finance, tailoring marketing strategies, or identifying process improvements, my role is about ensuring that data isn’t just numbers on a screen—it’s a tool that empowers teams and drives meaningful business growth.

Over the last few years, you’ve progressed into a Senior Business Intelligence Analyst role, how is that role different to a data analyst role?

The transition from Data/BI Analyst to Senior brought new responsibilities and a broader perspective. While a Data Analyst typically focuses on extracting insights and answering specific questions, the Senior role is more strategic. It’s about understanding the business at a higher level, aligning data strategies with company goals, and guiding others in their use of data.

In this role, I’ve gained more autonomy and now work closely with leadership teams to influence decisions directly. I’ve also taken on mentoring responsibilities, sharing my knowledge to help others grow. One key difference is the emphasis on translating insights into actionable strategies that drive long-term value.

It’s challenging at times—especially when you have to deliver insights that may be uncomfortable for stakeholders to hear—but it’s rewarding to see the trust and respect that comes from standing by your recommendations.

What would you say are the must have data analyst skills to thrive in today’s environment?

I believe to thrive as a data analyst today, you need more than technical expertise—you need passion, curiosity, and a deep understanding of the business. While skills like SQL and data visualization with Tableau or Power BI are essential, I’ve seen intelligent, non-technical individuals excel simply by asking the right questions and staying genuinely curious about the data they work with. A solid grasp of statistical concepts like means, medians, distributions, and outliers ensures efficient analysis, but it’s equally important to work closely with finance and stakeholders to define meaningful KPIs that reflect what the business truly needs to measure. The ability to adapt, spot details others might miss, and communicate clearly is what truly helps turn data into insights that drive impact.

How did you start improving your skills as a data analyst? What are you currently doing to keep up with the ever changing data analytics industry?

I started improving my skills by focusing on the basics—building a strong foundation in SQL, data visualization tools, and understanding statistical concepts. My degree in Mathematics, Statistics, and Operations Research gave me the technical background, but most of my growth came from working closely with stakeholders. Understanding their needs and challenges taught me how to align my analysis with real business goals.

I believe businesses move faster when you focus on what truly matters rather than constantly chasing the latest tools. I’ve been using the same tools for several years—SQL, Power BI/Tableau and Excel—and learn new ones when the business needs them. My approach has always been to understand the problem first and adapt my skills to solve it, rather than overcomplicating things.

To stay relevant, I observe what’s happening in the industry, keep an open mind to learning, and focus on building relationships with stakeholders to better understand what drives the business forward. For me, it’s not about knowing every tool but about staying curious and delivering insights that matter.

Can you share what factors are most important to you in a data-focused career and why? Do you have a vision of what you'd like your career growth to look like?

For me, the most important factors in a data-focused career are impact, growth, and alignment with the bigger picture. I believe data should be a tool that empowers teams to make better decisions and drives meaningful change within a business. Seeing the tangible results of my work—whether it’s optimizing a process, improving KPIs, or uncovering insights that no one saw before—is incredibly rewarding.

Growth is equally important to me, both in terms of learning new skills and taking on more responsibility. I’m always looking for opportunities to deepen my expertise while helping others better understand and use data effectively.

My long-term vision is to become a leader in the data space, someone who advocates for building data-first cultures and ensures that businesses not only collect data but truly leverage it to its fullest potential. I want to continue working in environments where curiosity and innovation are encouraged, and where I can help teams unlock the value hidden in their data.

What recommendations would you give to someone who is looking to join the data industry and get their first full-time data analyst position?

My recommendation for anyone looking to join the data industry is to focus on building a solid foundation and staying curious. Start with learning SQL and mastering at least one data visualization tool like Tableau or Power BI—these are fundamental skills that every data analyst needs. But more importantly, learn to think critically about the data you’re working with. Understand the business context, ask the right questions, and always be curious about the “why” behind the numbers.

I also believe it’s important not to focus too much on tools; instead, focus on understanding how data connects to the business. Having a basic grasp of statistical concepts like distributions and outliers can help you approach data logically and efficiently.

Finally, don’t aim for perfection—start where you are and be willing to learn as you go. Whether it’s through internships, small projects, or even personal experiments with data, the key is to get hands-on experience and show that you’re eager to grow. Curiosity, problem-solving, and a willingness to learn will take you further than you might expect.

Anything you'd like to highlight, or add? Something that is not specified above but you hear a lot, or would be helpful for people to know?

One thing I’d like to highlight is that data analytics is not just about technical skills. While knowing SQL or building dashboards is essential, I believe it’s equally important to understand the story behind the data and how it connects to real-world decisions. The ability to collaborate, communicate clearly, and approach problems with curiosity often makes a bigger difference than just being technically skilled.

I’ve also noticed that many people think they need to be perfect at everything before applying for a data role, but that’s not true. The field is constantly evolving, and the best analysts are those who are willing to learn, adapt, and grow with the industry. Don’t be afraid to start small, ask questions, and embrace challenges—they’re what shape you into a great data professional.

An extra one: How do you see the increased availability of AI tools such as ChatGPT, Bard etc., impacting the typical data analyst role / or of someone in data analytics? Are you using AI tools to augment your thinking, analysis and overall work?

I think the increased availability of AI tools is changing the landscape of the data analyst role in exciting ways. These tools can handle repetitive tasks, like cleaning data or generating basic reports, which allows analysts to focus more on strategic and creative problem-solving. However, I don’t see AI replacing analysts—it’s more of an assistant that helps enhance our thinking and speed up workflows.

Personally, I use AI tools like ChatGPT to help me refine my documentation, brainstorm ideas, and even confirm my understanding of technical concepts. It’s particularly useful for structuring my thoughts when I’m juggling multiple priorities. That said, AI isn’t perfect; it can make mistakes, and it’s up to us to critically evaluate its outputs.

Ultimately, AI is a tool, not a replacement for human expertise. A good analyst knows how to ask the right questions, think critically, and interpret data in a way that no tool can fully replicate. If anything, these tools make our work more efficient and allow us to focus on the aspects of data that truly drive value.

This has been great, thank you again, Maria. Where could people see more of your work, and connect with you?

https://www.linkedin.com/in/maria-balzan