What Does a Data Scientist Do?

Updated 12 August 2023

A data scientist extracts insights from data to aide decision-making. Data scientists have become more common and in demand, as big data continues to be increasingly important to the way organizations make decisions.

An individual coding at their desk with laptop on the left and two monitors on the right.

Data science might be the one for you if you enjoy:

Spotting patterns and uncovering insights through analytical exploration
Thinking logically when analysing and interpreting data
Working with numbers and that includes statistical concepts, algorithms, and mathematical models
Paying attention to the small details when working with large datasets

What is data science?

Data science is the collection, cleaning, analysis, visualization, and interpretation of data to inform decision-making and solve complex problems across diverse industries.

Many data scientists can begin their careers as data analysts or statisticians.

How is data science different to data analysis?

Data scientists are often expected to form their own questions about the data, while data analysts might support teams that already have set goals in mind. A data scientist might also spend more time developing models, using machine learning, or incorporating advanced programming to find and analyze data.

Core Tasks and Resposibilities

Some of the day-to-day tasks and responsibilties of a data scientist might include:

Collecting and cleaning data.
Analysing data to uncover patterns, trends and outliers.
Building predictive and prescriptive models using machine learning and statistical techniques to solve complex problems.
Creating compelling visualizations to communicate insights to both technical and non-technical stakeholders.
Drawing actionable conclusions from data analyses and translating them into strategic recommendations.
Working closely with cross-functional teams to align data-driven insights with business objectives.

What do you learn?

A data science course would typically teach you:

How to handle, clean, analyse and visualise data.
Languages such as Python and/or R and tools such as pandas, NumPy, scikit-learn, and Jupyter notebooks.
Understanding machine learning fundamentals, such as, algorithms for classification, regression, clustering, and more.
Model evaluation and deployment.

Are you looking to become a data scientist? If you are naturally curious, have an aptitude for Maths and comfortable with large datasets, data science could be the perfect fit for you.

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