To understand the role of the data scientist, you first have to understand what data science is.
As the
media update team wrote in a previous article,
What is data science?, this field combines mathematics, programming, problem-solving, and data capturing. It is also the process of finding patterns in data, along with cleaning, preparing, and aligning data.
Now we take a look at the person that typically makes data science happen:
A definition of “data scientist”
A data scientist is a person who uses analytical, statistical, mathematical, programming, and business skills to collect, analyse, and interpret large data sets to find solutions for businesses. They use databases, coding, and
machine learning to draw conclusions that can help companies and organisations.
One of the main goals of a data scientist is to connect data with business outcomes to drive strategic decisions. This aspect of the role has been recognised for decades. In 1997, Chien-Fu Jeff Wu, then a faculty member of the University of Michigan,
explained that statistical work – or what he called data science – uses a trilogy of data collection, data modelling and analysis,
and decision-making.
The role of a data scientist should not be confused with a
data analyst’s role. Analysts also find the right data sets, clean the data, and extract information from it, Akshatha Kamath at
Simplilearn writes. But they don’t necessarily build statistical models or use machine learning and advanced programming to find business insights.
Data scientists are also different from
data engineers, a
DataCamp blog post notes. Engineers are involved in developing and maintaining technology such as databases and large-scale processing systems – which house the data that the scientist uses.
What data scientists do:
The role of the data scientist emerged because more and more data has become available to businesses. Companies have realised that the Big Data available to their operations, customers, target market, industry, and competitors has value.
Without the help of an expert, extracting information from this data can be a labour-intensive, manual task for businesses.
This is where the data scientist steps in.
Sarah K. White
writes in an article for CIO that
data scientists:
- Identify business problems and opportunities that can be solved by data insights
- Find the correct data sets that can provide the answer to these problems
- Clean and prepare these data sets
- Choose models and algorithms that are able to process the data for a specific purpose
- Analyse the results delivered by these models and algorithms for patterns
- Connect the patterns, or trends, in the data to business solutions, and
- Share this information with the decision makers of the business in a way that is easy to understand and actionable.
The information helps companies and organisations become more efficient, make more sales, gain more customers, and expand into new industries.
As the data created by human activities continue to grow, these specialists will play a more important role in exploiting this information to produce better products, services, and business results.
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