Defining a Data Scientist

A data scientist is the adult version of the kid who can’t stop asking “why?” They’re the kind of person who goes into an ice cream shop and gets five different scoops on their cone because they really need to know what each one tastes like…

Defining a Data Scientist

The author(s)

  • Leo Cremonezi Ipsos Connect, UK
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It’s been said that Data Scientist is the “sexiest job title of the 21st century.” But, why is it such a demanded position? The short answer is that over the last decade there’s been a massive explosion in both the data generated and retained by companies, and individuals. Sometimes we call this “big data,” and like a pile of lumber we’d like to build something with it. Data scientists are the people who make sense out of all this data and figure out just what can be done with it.

Data science is a multidisciplinary field that combines the latest innovations in advanced analytics, including machine learning and artificial intelligence, with high-performance computing and visualisations. The tools of data science originated in the scientific community. Over the past decade computing costs have shrunk and software has become more sophisticated, causing data science to gradually enter business, government, and other sectors.

Any company, in any industry that crunches large volumes of numbers possesses lots of operational and customer data. They may also have access to that data generated by social media streams, credit data, consumer research, or third-party data sets. Companies with data on this scale can benefit from having a data scientist, or a data science team.

Most data scientists have advanced degrees and training in maths, statistics, and/or computer science. Most likely they have experience in data mining, data visualisation, and/or information management. Previous work with cloud computing, infrastructure design, and data warehousing is also common. On a personal level, they are highly curious and passionate about problem solving and accuracy.

Put simply, data scientists apply powerful tools and advanced statistical modelling techniques to provide solutions and insights about business problems, processes, and platforms. But, let’s be clear: big data is not a science project. Rather, it must be operationalised in specific ways through more personalised offers to customers and prospects, better insight into pricing trends, and closer tracking of customer behaviours across channels. However, to do this effectively and efficiently at a larger scale requires that someone continuously seek the highest performance and rethink the possibilities afforded by the data.

Therefore, data scientists are the ones experimenting with intelligence-gathering technologies, developing sophisticated models and algorithms, and combining disparate data sets. They will ask the biggest most improbable-seeming questions. They will lead the deepest data mining expeditions and boldest explorations into the largest and most diverse data sets. Or maybe just help you identify the whiskies you might like best.

They also enrich data’s value, going beyond what the data says to what it means for your organisation. In other words, it turns raw data into actionable insights that empower everyone in your organization to discover new innovations, increase sales, and become more cost-effective. Data science is not just about the algorithm, but about deriving value.

But, what do the capabilities of data science mean for businesses? Businesses are continually seeking competitive advantage, where there are multiple ways of using data to underpin strategic, operational, and execution practices. Business personnel today, especially with millennials (comfortable with the open-ended capacities of Siri, Google Assistant, etc.) entering the workforce, expect an intelligent and personalised experience that can help them create value for their organisation. In short, data science drives innovation by arming everyone in an organisation, from frontline employees to the board, with actionable insights that connect the dots in data. This brings the power of new analytics to existing business applications and enables new intelligent applications.

Data scientists bring a critical set of problem-solving skills companies need to win with data, but they are just one piece of the puzzle that must be complemented by executive sponsors, marketing data experts, and business analysts, each of which have similarly important roles to play.

The author(s)

  • Leo Cremonezi Ipsos Connect, UK

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