What is a Data Scientist?

A data scientist is someone who can use data to draw out key insights for better problem solving and decision making. Combining skills from statistics, computer science and specific domain knowledge they derive patterns and understanding from raw data.

What do Data Scientists Do?

What most people think Data Scientists Do

A cartoon image of what most people think data scientists do: analyse data and create models.

What Data Scientists Actually Do

A tongue in cheek image entitled "The Endless Cycle of Data DESPAIR". It includes many tasks data scientists do with arrows interconnecting them. These include: Collect data, clean data, standardise data, productionise models and communicate findings

How Do Data Scientists Work Their Magic?

  • Equations and graphs on a chalkboard, representing mathematical and statistical concepts in data science education.

    Maths and Stats

    Data Scientists make use of a number of tools from mathematics/statistics to computer programming to those considered softer skills. Some skills from the world of statistics include:

    • Linear Algebra

    • Probability Theory

    • Regression

    • Feature Engineering

    • Artificial Intelligence/Machine Learning

    Want to learn more? We explain about all of these topics over on our data science blog.

  • Computer monitor displaying Python code, illustrating programming skills essential for data scientists.

    Computer Science

    Some skills from the world of computer science include:

    • Programming, usually in Python or R

    • Distributed programming for big data

    • Data Science packages such as pandas, polars, sk-learn, keras, numpy

    • Data Structures

    • Databases

  • Disassembled Lego person, symbolizing problem-solving and critical thinking soft skills for data scientists.

    Softer Skills

    Finally, an underestimated set of skills are the so-called “soft skills” needed for a data scientist to become a valuable asset to the team, instead of just a nerd in the corner. These skills include:

    • Critical Thinking

    • Problem Solving

    • Communication, technical and non-technical

    • Project Management

Where Do Data Scientists Work?

  • Data Scientists work in a variety of industries

    And with the recent AI boom, data scientists are becoming more and more in demand, with industries that would never have considered hiring them before taking steps to branch out. Some of the more common places where you would find data scientists include:

  • Glass skyscrapers in a major city, representing the finance industry where data scientists manage risk.

    Finance

    From the classical Quantitative Analysts (who are basically data scientists with a more probability and statistics lean) to modern day machine learning engineers, the finance industry is full of technical people using advanced data science to manage risk, inform trading decisions and understand the financial world better.

  • A friendly white robot, symbolizing Artificial Intelligence and the tech industry's need for data scientists.

    Tech

    From algorithm wizards working on content recommendation systems to those pushing the frontier of Artificial Intelligence, the tech industry is ripe with opportunities for Data Scientists to flex their technical skills and drive the profession further forward.

  • Healthcare workers in scrubs using technology, showing data science analysis of patient records for better diagnosis.

    Healthcare

    The healthcare industry has two things that make it ripe for data science innovation: the mass of patient data and meaningful real-world problems to solve. Analysis of both organisational and symptom data can drive better outcome for patients and the use of Artificial Intelligence to help in the diagnosis process is only increasing.

  • A shopper looking at shelves, illustrating how data scientists use forecasting for retail supply chain optimization.

    Retail

    How do big retailers know when strawberries will be most popular? Or the latest toy trend that will drive purchases this Christmas? The retail industry employs hundreds of forecasters using data science techniques to optimise supply for predicted demand to ensure that customers can get what they want, when they want it, whilst minimising waste.

  • Trucks with shipping crates, symbolizing logistics and supply chain management optimized by data scientists.

    Logistics

    When it comes to logistics and supply chain management, there are a huge number of moving parts. The more moving parts, the more opportunities for inefficiencies to sneak in. In addition, the complexity means a huge data challenge, giving data scientists the opportunity to optimise this process and remove inefficiencies within the supply chain.

  • An oil tanker at sea, representing data science applications in oil and gas exploration and efficient extraction.

    Oil and Gas

    From improving exploration of potential sources to more efficient methods of extraction, to optimising delivery to receive the best price for extracted oil and gas, there are many points in the oil and gas pipeline in which data science involvement can add value.

  • And many more

    And this is by no means an exhaustive list. We see more data science openings in governments, marketing, e-commerce and sport analysis. As the utility of data science becomes more prevalent, we see it making inroads to more and more industries, such as gaming, mass media, education, culture and many more.