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In Australia, the demand for data scientists has increased significantly, with job postings rising by 200% in five years (JobNow Australia, 2023). If you’re an engineer looking to transition to a data scientist, you totally have an advantage. Engineers have a natural analytical mindset, proven abilities with problem solving, and a vast amount of technical skills that will be the foundation of your career shift.
How do you get started? When can you expect to transition to a career in data science? What skill sets should you focus on to ensure your success in the transition? This blog will cover what you should know to propel your career in data science, dealing specifically with engineers who want to work as data scientists in Australia.
Data science involves leveraging data to create value and extract meaning from larger datasets to be applied in the world of business. Data scientists spend most of their time, compared to engineering roles, building predictive models and data visualizations that include outcomes that will help the business in its decision-making.
We develop high-quality Career Episodes, quality Summary Statements, and solid CPD reports that meet Engineers Australia’s standards of competency in your CDR.
Experience Level | Annual Salary Range (AUD) | Â Responsibilities |
Entry-Level Data Scientist | $80,000 – $100,000 | Data cleaning, basic analysis, learning from senior team members, working on guided projects |
Mid-Level Data Scientist | $110,000 – $140,000 | Building machine learning models, leading small projects, mentoring juniors, stakeholder communication |
Senior Data Scientist | $150,000 – $180,000+ | Complex model development, strategic decision-making, project leadership, cross-team collaboration |
Lead/Principal Data Scientist | $180,000 – $220,000+ | Team leadership, architecture decisions, business strategy, high-impact projects, mentoring data science teams |
We assist engineers worldwide with CDR preparation, RPL reports, VETASSESS documentation, CPD writing, and resume development, providing everything required for a smooth Australian PR journey.
CDRAustraliaEngineer provides end-to-end support for Engineers on the pathway to a Career in Data Science, including personalized learning pathways, projects, skills assessment recommendations, and techniques for getting into the Australian data science industry faster.
Building a successful career in data science requires both technical and soft skills. Here’s what you needÂ
Category | Topic | Description |
Core Programming Languages | Python | Python is the most popular programming language for data science because of its powerful libraries such as Pandas, NumPy, and Scikit-learn. |
SQL | Essential for querying and working with relational databases. | |
R | Especially useful for statistical analysis, often used in research-heavy roles. | |
Statistical and Mathematical Knowledge | Descriptive Statistics | Understanding distributions, means, and standard deviations. |
Inferential Statistics | Hypothesis testing and p-values. | |
Linear Algebra | Key for understanding many machine learning algorithms. | |
Probability Theory | Foundation for many statistical models and machine learning techniques. | |
Machine Learning Fundamentals | Supervised and Unsupervised Learning | Including regression, classification, and clustering. |
Model Evaluation | Techniques like cross-validation and performance metrics (e.g., precision, recall). | |
Feature Engineering | Creating meaningful features from raw data. | |
Model Deployment | Turning models into real-world applications. | |
Data Visualization and Communication | Visualization Tools | Tools like Matplotlib, Seaborn, Tableau, and Power BI are critical for presenting data in a way that’s accessible to stakeholders. |
Storytelling with Data | Being able to present complex data insights in a clear and compelling way. |
We help you professionally present your career with customized resumes, career episodes, summary statements, and CPD documents tailored for Engineers Australia.
Starting a career in data science provides an exciting opportunity for engineers with many useful and relevant skills. With appropriate learning, practice, and commitment, it is possible for engineers to transition quickly in a meaningful way to this quick-changing field and to succeed.
At CDR Australia Engineer, we support engineers wherever they are in their careers, including if they are heading to a career in data science. Take the first step today; it could be taking an online Python course, developing something in your own time, or attending a meetup with local people. The good news is, your engineering background will place the groundwork for you to succeed in the world of data science.
Job boards such as Seek, LinkedIn Jobs, Indeed Australia, Glassdoor Australia, and Digital Resources Australia are all targeted to data science disciplines in Australia.
The best online courses are “IBM Data Science Professional Certificate” on Coursera, “Data Scientist with Python Career Track” on DataCamp, and “Machine Learning” by Stanford University on Coursera.
No, you do not need a master’s degree to get started. Many data scientists begin with a bachelor’s degree or through self-taught skills, development, and projects.
Typically it takes between 6 and 12 months with 10-15 hours a week for study. Sometimes software engineers and related professionals will transition faster by 4-6 months.
The main ANZSCO code for a Data Scientist is 224115 – Data Scientist. In some instances, the Australian Computer Society (ACS) will use the code 224999 (Information and Organization Professionals, NEC) if your specific role does not fall in the general occupation description.
