In a digital world companies need to utilize technology, knowledge, computational power and access to data, whilst recognizing that insights are the new business currency.
Data scientists are a relatively new breed of analytical data expert who have the technical skills to solve complex problems – and the curiosity to explore what problems need to be solved. They help to connect data to business outcomes.
They’re part mathematician, part computer scientist and part trend-spotter (of course they are more than this with diverse backgrounds and areas of expertise. They straddle both the business and IT worlds to help the whole organization make better business decision and actions across the entire value chain. They are pioneers daring to go where no person has gone before...pinning them to a specific coding language or ML or any specific part of the broader AI ecosystem is foolhardy. They’re highly sought-after and well-paid. Who wouldn’t want to be one?
They’re also a sign of the times. Data scientists weren’t on many radars a decade ago, but their sudden popularity reflects how businesses now think about big data. That unwieldy mass of unstructured information can no longer be ignored and forgotten. It’s a virtual gold mine that helps a business solve challenges across the entire value chain – as long as there’s someone who digs in and unearths business insights that no one thought to look for before. Enter the data scientist.
Many data scientists began their careers as statisticians or data analysts. But as big data (and big data storage and processing technologies such as Hadoop) began to grow and evolve, those roles evolved as well. Data is no longer just an afterthought for IT to handle. It’s key information that requires analysis, creative curiosity and ability to translate ideas into actionable insight driving better, faster decision-making for improved outcomes for all business activities. Data enabled business models mean companies do not have to guess anymore.