In Playmaker Spotlight, we get up close (and sometimes personal) with a valuable team member whose individual contributions shouldn’t be overlooked but instead used to highlight their unique experience. Besides taking this great opportunity to share their accomplishments with the world, we also hope to provide you with insider info about our team culture and what it’s like to work at Databox. Today, data science represents the foundation of smart decision-making for many growing businesses. A couple of years ago, we embraced its transformative power with Miha Pavlinek, our Director of Data Science and Engineering, leading the change. The main strategy of his team includes harnessing data to help businesses thrive using data science. In this blog, we’ll let Miha explain how data science fuels innovation at Databox. A Journey towards Data Before joining Databox, Miha spent nearly a decade as a teaching assistant, combining hands-on experience with research-driven projects. Since he has always been fascinated with large datasets and the hidden patterns within them, a journey towards data, algorithms, and machine learning seemed natural. After completing his PhD, Miha decided to transition into the industry to gain experience as a data scientist across a variety of projects, including fraud detection, recommendations, time series analysis, forecasting, customer analysis, and more. His evolution into advanced analytics eventually led him to Databox, where he got the chance to combine his expertise with our vision of leveraging data science to empower businesses. The Role of Data Science in Modern Business Intelligence In recent years, data science has revolutionized business intelligence (BI) by elevating traditional BI tools with advanced features like predictive modeling and machine learning. As Miha states, “modern BI tools are no longer limited to dashboards, visualizations, and reports, but instead deliver actionable insights, accurate predictions, and personalized recommendations. This enables businesses to make smarter, real-time decisions—an essential part of our mission at Databox.” This shift has allowed small and medium-sized businesses to access data-science-driven tools and functionalities, allowing them to maintain a competitive advantage. “At Databox, this evolution has not only reshaped our approach to product development but also redefined how we think about the future of BI.” Building a Data Science Team that Drives Impact In recent years, the Databox data science team has evolved from its roots in data engineering to become an integral part of the product team. This strategy ensures the team stays closely aligned with customer needs, creating features like forecasting, anomaly detection, and generative AI solutions that directly enhance user experience. The team is primarily responsible for developing advanced data solutions within our products. These solutions provide our customers with additional insights from their own data in the form of patterns, trends, and relationships. This enables them to uncover new findings, make better business decisions, and gain a competitive advantage. By focusing on solutions based on advanced modeling, machine learning, and statistical methods, the team empowers customers to make data-driven decisions with confidence. They focus on features that allow us to attract more demanding customers on higher pricing plans, which significantly impact our success. “In a way, data science not only shapes the future of our product but also plays an important role in driving growth and delivering value to our customers.” Charting the Future of Data Science When planning for the future, Miha envisions a dynamic future for data science within Databox. As the company scales, so does the complexity of its challenges. Since the industry has been recently shaken by a new wave of technologies led by generative AI, we want to address this topic more intensively. The Data Science team has already begun to concretely utilize these technologies in our products. In the next phase, they will focus primarily on autonomous AI agents or agent systems that independently perform specific tasks, thereby providing better input for AI features.On the other hand, with new data engineering initiatives, we are moving from a point where we only offered metrics to processing and providing raw data. “These efforts will result in data quality improvements and will also enable us to deliver new data features such as conversational analytics, AI-assisted metric creation, or highlighting anomalies in raw data, making the role of data science within Databox increasingly more important.” Bridging Vision and Execution For Miha, data science is about more than just algorithms or dashboards. It’s about making information accessible, actionable, and impactful. The work of Databox’s data scientists ensures that we remain at the forefront of BI innovation, empowering teams, customers, and the company as a whole to thrive in a data-driven world.