Become aPredictive Modeler

So, why should you become a Predictive Modeller? First of all, it’s incredibly rewarding to see your predictions come true and know that your work is making a real difference. Plus, it’s a dynamic industry where there’s always something new to learn. And let’s not forget, it’s a career that offers great opportunities for growth and advancement, with plenty of industries to explore.

In this career you can combine your passion for numbers with your creative skills by working at the cutting edge of technology, using advanced tools and techniques to make accurate predictions that can help shape the future.

• Predict future trends and outcomes with data
• In-demand skills across industries
• Solve real problems using advanced statistics
• Shape business decisions with your insights

As a Predictive Modeller, you’ll analyse past data to make predictions about the future.  It’s a role that requires both technical skills and creativity, as you’ll need to design models that are both accurate and innovative.

This involves:

• Using statistical techniques and machine learning algorithms to identify patterns and trends in the data. 
• Creating models that can forecast everything from consumer behaviour to financial markets, helping businesses and organisations make better decisions.

Predictive Modellers are in high demand across a variety of industries. Wherever there’s data, there’s a need for skilled professionals who can turn it into valuable insights.

Finance

Predicting share, stock and cryptocurrency market trends and managing risk.

Retail

Forecasting customer behaviour and optimising inventory.

Healthcare

Predicting disease outbreaks and improving patient care.

Technology

Enhancing user experiences and personalising content.

Sports

Analysing player performance and predicting game outcomes.

Weather Services

Forecasting weather patterns and natural disasters.

To succeed as a Predictive Modeller, you’ll need a blend of technical skills and personal attributes. Here are some key skills you’ll need to develop.

• Statistical Analysis
• Programming (e.g., Python, R)
• Machine Learning
• Data Visualisation
• Critical Thinking
• Problem Solving

Choosing the right  STEM subjects in school can set you on the path to becoming a successful Predictive Modeller. Here are some key subjects that will help you build the necessary skills.

Mathematics

Develop your analytical and statistical skills.

Computer Science

Teaches you programming and data handling.

Statistics

Essential for understanding data analysis techniques.

Economics

Helps you understand market trends and economic models.

Physics

Enhances your problem-solving and analytical thinking.

Business Studies

Provides insights into how businesses use data for decision-making.

As a Predictive Modeller, you’ll get to work on some really cool projects. You could help a sports team improve their performance by analysing player statistics, or predict the next big trend in fashion for a retail company.

Predict the next viral internet trend

Use algorithms to track online behaviour and predict which TikTok challenges or memes will go viral next.

Help cities plan for the future

Model urban growth and transportation needs, predicting how cities like Perth or Melbourne will expand in the next decade.

Optimise gaming experiences

Work with gaming companies to predict player behaviour and create personalised gaming experiences that keep players engaged.

Forecast the success of a new product

Use data to help businesses predict which new products will succeed, based on customer preferences and market trends.

Model wildlife populations

Use predictive modelling to forecast how wildlife populations will change in response to climate change or habitat loss, helping conservation efforts.

Design algorithms for personal assistants

Work with AI to improve virtual assistants like Siri or Alexa, predicting user needs and creating smarter, more intuitive tools.

Australia has produced some incredible Predictive Modellers who have made significant contributions to the field. 

Dr. Cathy O’Neil

Known for her work in data science and predictive modelling, particularly in the areas of finance and risk management. 

Dr. Genevieve Bell

A renowned anthropologist and technologist, Bell is a leader in data science and AI, using predictive modelling to understand human behaviour in the digital world.

Dr. Kate Saunders

Specialising in financial and economic forecasting, Saunders uses predictive models to shape investment strategies and business decisions.

Professor Louise Ryan

An award winning statistician, Ryan is known for her work in environmental health and predictive modelling for public health outcomes.

Dr. Karen Lamb

A leader in health analytics, Lamb applies predictive modelling to improve health outcomes, particularly in chronic disease management and public health planning.

Being a Predictive Modeller isn’t just about having the right skills – it’s also about having the right personality traits to succeed in this challenging and rewarding career.

• Curious
• Analytical
• Creative
• Detail Oriented
• Persistent
• Collaborative

Bachelor of Science in Data Science

A solid foundation in predictive modelling often starts with a degree in data science, statistics, or mathematics. Curtin University offers a Bachelor of Science in Data Science, which covers essential topics such as statistical modelling, machine learning, and big data analysis. This provides students with the tools to analyse complex datasets and build predictive models.

Master of Data Science

For those wanting to specialise, postgraduate degrees such as the Master of Data Science at the University of Western Australia (UWA) offer more advanced coursework in predictive modelling, AI, and machine learning. These courses delve into real life applications, preparing students for complex data challenges.

One of the coolest things about becoming a Predictive Modeller is that you can blend different fields of study to create a unique educational pathway. 

Combining Computer Science with Economics can give you a solid foundation in both the technical and economic aspects of predictive modelling. This approach not only broadens your knowledge but also makes you more versatile in the job market.

Pair Mathematics with Social Sciences to understand human behaviour patterns and predict trends in society. Or how about mixing Data Science with Environmental Studies? This combination can help you tackle important issues like climate change by predicting environmental impacts.

By combining different subjects, you can develop a well-rounded skill set that makes you a valuable asset in many industries. Plus, interdisciplinary studies often involve collaborative projects, giving you the chance to work with students from other fields and learn how to communicate complex ideas effectively.

During your studies, you’ll learn a variety of skills like:

• How to collect, analyse, and interpret data to make accurate predictions.
• Statistics and probability, mastering techniques to model and forecast future events. 
• Programming languages like Python and R become essential tools in your toolkit. 
• Machine learning algorithms and how to apply them to current problems. 
• Data visualisation to turn complex data sets into easy-to-understand charts and graphs is a vital skill for any Predictive Modeller.

Work experience helps you gain in person experience. Look for projects where you can apply predictive models to business, health, or environmental data. Positions like Data Analyst or Junior Data Scientist are great starting points, allowing you to build your skills in data cleaning, statistical analysis, and predictive modelling before moving into more advanced roles. For example, you could intern at a tech company, helping to develop predictive models for user behaviour, or work with a retail business to forecast sales trends. Work experience not only enhances your resume but also helps you build valuable industry connections.

Not keen on spending years at university? No worries! There are alternative pathways to becoming a Predictive Modeller that can be just as effective.

Online Courses and Certifications

To sharpen your skills or transition into predictive modelling, online platforms like Coursera or edX offer certifications in machine learning, data analytics, and predictive modelling. These courses often come with practical exercises that mimic real-world problems.

Industry-Specific Certifications

Certifications in cloud computing or data analytics from platforms like AWS or Google Cloud can also enhance your expertise, making you more attractive to potential employers.

Attending Industry Events and Meetups

Attend industry events such as the Data Science and AI Summit or local meetups to learn from experts and connect with professionals in the field. Networking can help you stay on top of new trends and open doors to job opportunities.

Joining Professional Associations

Joining organisations like the Statistical Society of Australia or the Australian Data Science Network can give you access to valuable resources and connections in the field of predictive modelling.

Microlearning

Microlearning involves taking short, focused courses on specific topics. Platforms like Coursera, Udemy, and edX offer courses in data science, machine learning, and predictive analytics. These courses can help you build your skills step-by-step and at your own pace.

Predictive Modellers are in high demand across Australia, with opportunities spanning diverse industries and locations.

Western Australia

In Western Australia, Predictive Modellers are in demand in sectors like mining and natural resources. These industries rely on predictive analytics to optimise operations and forecast market trends. You could find opportunities working with companies to improve efficiency and predict future demands.

Australia

Across Australia, you’ll find a wealth of opportunities in finance, healthcare, and retail. Financial institutions need Predictive Modellers to manage risks and forecast market movements. In healthcare, you could work on predicting disease outbreaks or patient outcomes. Retail businesses use predictive models to understand consumer behaviour and optimise inventory.

Rest of the World

Globally, Predictive Modellers are needed in virtually every industry. From tech giants in the USA to innovative startups in Europe, the skills of a Predictive Modeller are highly valued. You could work for companies developing leading AI technologies, or in the public sector, helping governments make data informed decisions.