How to become a Data Scientist

Data Scientist

A data scientist is responsible for translating raw data into information that solves problems. Using specific tools, a data scientist extracts data from a range of sources, in order to analyse, interpret, and uncover insights.

Data is an incredibly valuable business resource, and organisations are increasingly looking to harness data science to improve their operations. That’s where a data scientist comes in.

 The field of data science is focused on discovering the patterns in raw data and using tools, algorithms, and machine learning to turn that data into valuable business insights. A data scientist sits within this field, with a specific focus on not only gathering the data, but studying it from new angles.

A data scientist’s role will vary depending on the organisation and industry, but can encompass everything from data collection and innovative analysis, to building data modelling software and presenting information using state-of-the-art data visualisation techniques.

Working in data science requires creativity, critical thinking and problem-solving skills. You’ll need to be able to take complex data, analyse it and then explain your findings to your colleagues using clear and straightforward language.

What degree is most commonly held by a Data Scientist?


  • Phd, Computer Science
  • Phd, Data Science
  • Phd, Physics
  • Phd, Statistics
  • Phd, Economics
  • Phd, Mathematics
  • Phd, Mechanical Engineering
  • Phd, Information Technology
  • Phd, Chemical Engineering
  • Phd, Electrical and Electronics Engineering
  • Phd, Applied Mathematics
  • Phd, Electrical Engineering
  • Phd, Mathematics and Statistics
  • Phd, Psychology
  • Phd, Artificial Intelligence
  • Phd, Bioinformatics
  • Phd, Machine Learning
  • Phd, Business Analytics
  • Phd, Computer Engineering
  • Phd, Finance
  • Phd, Engineering
  • Phd, Actuarial Science

Career Transportability across Countries


Transportability: Medium
A data scientist is a specialised role, but many of the skills are transferable to other career paths. The key assets of a data scientist, a combination of technical, analytical and communication skills are valuable in fields such as computing, analytics or marketing. In addition, there are a number of different careers within data science itself. Data analyst, data engineer or business analyst roles all sit within data science but have different areas of focus. The key skills of a data scientist, primarily the ability to understand and interpret data sets, is easily transferred to these types of roles.

What is the Salary of a Data Scientist?

ExperienceEducationAverage salary | year
AU$UK£US$
Junior1-3 yrs€70,254£34,000$40,216
Mid-Level1-4 Yrs€76,790£40,000$49,868
Senior5+ Yrs€88,226£51,000$60,592
Data Science Director10 Yrs€119,268.87£102,417$150,098

What skills are needed to become a Data Scientist?


  • SQL
  • Python
  • Data Analysis
  • Machine Learning
  • R
  • Statistics
  • Research
  • Microsoft Excel
  • Matlab
  • Data Science
  • Microsoft Office
  • Data Mining
  • Java
  • C++
  • Tableau
  • Data Visualization
  • Project Management
  • Statistical Modeling
  • Programming
  • Analytics
  • Management
  • LaTeX
  • Big Data
  • Deep Learning
  • Leadership

Data Scientist Courses

Discover courses from leading academic and cultural institutions that are related to a career as a data scientist. These courses are designed for those people at the beginning of their career in data science or those who are switching from a different career path.
  • Data to Insight: An Introduction to Data Analysis and Visualisation

    Get a handson introduction to data science exploring principles of statistical analysis and data visualisation

  • Big Data: Measuring And Predicting Human Behaviour

    Join us to explore how the vast amounts of data generated today can help us understand and even predict how humans behave

  • Introduction to Data for Business Leaders

    A leadership course that goes beyond the hype surrounding data by focusing on the practicalities of achieving business outcomes

  • Introduction to R for Data Science

    Discover big data work with airline data to learn the fundamentals of the R platform

  • Data Science in the Games Industry

    Learn how the games industry can use big data to enhance the gaming experience and increase profits

  • Big Data Analytics: Opportunities, Challenges and the Future

    We produce more data than ever before Find out how big data analytics can help you make use of it

  • Data Mining with Weka

    Discover practical data mining and learn to mine your own data using the popular Weka workbench

  • Advanced Data Mining with Weka

    Learn how to use popular packages that extend Wekas functionality and areas of application Use them to mine your own data

  • Managing Big Data with R and Hadoop

    Learn how to manage and analyse big data using the R programming language and Hadoop programming framework

Data Scientist Microcredentials

  • Data Science: Data-Driven Decision Making

    Discover storytelling with data and make better business decisions using data wrangling modelling and visualisations in R

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