I’m wondering if moving into operations analytics is a good first step for someone who eventually wants to become a Data Scientist. Does working with KPIs, reports, and business data make the transition easier, or would the jump to statistics and machine learning still be quite big? Would love to hear from anyone who’s taken this route.
Yes, operations analytics can be a great stepping stone to data science. Working with KPIs, reports, and business data helps you develop analytical thinking and understand real-world business problems. That experience will be useful when you start working on more advanced data projects.
The jump to data science does involve additional learning, especially Python, statistics, probability, and machine learning. I’d suggest building a strong foundation in Excel, SQL, and Power BI first, then gradually moving into Python and ML projects using operational data.