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…
It’s been said that 'Data Scientist' is the “sexiest job title of the 21st century.” Why is it such a demanded position these days? The short answer is that over the last decade there’s been a massive explosion in both the data generated and then retained by companies. 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, where researchers used them to test and verify hypotheses that include “unknown unknowns,” and they have entered business, government, and other organisations gradually over the past decade as computing costs have shrunk and software has grown in sophistication.
Any company, in any industry, that crunches large volumes of numbers, possesses lots of operational and customer data, or can benefit from social media streams, credit data, consumer research or third-party data sets 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 fairly 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 make discoveries 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 those things more effectively and efficiently, at larger scale and with more precision, requires that someone continuously seek the leading edge in terms of performance and constantly rethink what is possible with the data available.
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. They will seek the black swans lurking in your data streams. Or maybe just help you identify the whiskies you might like best.
They also enrich the value of data, going beyond what the data says to what it means for your organisation—in other words, it turns raw data into intelligence that empowers everyone in your organization to discover new innovations, increase sales, and become more cost-efficient. Data science is not just about the algorithm, but about deriving value.
But what do the new data science capabilities mean for business users? Businesses are continually seeking competitive advantage, where there are a multitude of ways to use data and intelligence to underpin strategic, operational, and execution practices. Business users 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 intelligence that connects the dots in data, bringing the power of new analytics to existing business applications and unleashing new intelligent applications.
These warriors bring a critical set of problem-solving skills companies need to win with data, but it’s just one set, that must be complemented by executive sponsors, marketing data experts and business analysts, each of which have similarly important roles to play.
Leo Cremonezi - Statistical Scientist, Teacher and Mentor, Ipsos Mori