Tailored career navigation for different needs and audiences.
Discover our three-pillar approach to transforming career guidance
We combine deep scientific insights with scalable technology to help individuals and enterprises explore the future of work connecting their interests to emerging industries, skill paths, and real-world opportunities.
We combine a range of data sources – from big longitudinal workforce data to real-time data from job postings and online platforms – to ensure every career recommendation is grounded in evidence, not guesswork.
From schools to workforce agencies, Jobography is built for large-scale impact, not as a public job board, but as a strategic institutional tool.
The First AI career navigation platform built around the individual, but scalable for teams, schools, and enterprises.
Jobography is an intelligent career navigation platform that uses AI to map and match your skills to jobs, courses, and career pathways, visualizes multiple opportunities, and guides you toward actionable next steps — helping you explore, compare, and plan your future with confidence.
In Jobography, occupations are grouped into categories and coded using a system called the International Standard Classification of Occupations (ISCO-88). This system helps make occupation comparisons easier across different countries, while sorting occupations from high-skill, high-paying ones at the top, to lower-skill, lower-paying ones at the bottom.
Before converting occupations into this international scale, they were first grouped and coded using the ANZSCO system (Australian and New Zealand Standard Classification of Occupations), which was developed by the Australian Bureau of Statistics (ABS), Statistics New Zealand, and the Australian Government's Department of Employment and Workplace Relations.
No. Jobography doesn't guarantee what job you'll get or how much you'll earn, but it can give you a useful guide.
The occupation projections on the map are based on trends from past years, using publicly available data and in-house proprietary data from JobSciences Pty Ltd. This means it looks at what has happened before, including which jobs have grown, the median hourly wage for people in each occupation, and how people have moved between occupations.
Altogether, it can help you explore your options, understand what different jobs might pay, and see how others have moved through their careers.
Jobography can be a great tool for planning your next step. Even though it doesn't give you courses or training directly, it helps you see where you are now and where you could go next. Here's how it can support your self-upgrade journey:
Predictions are based on real data and patterns from how people have moved through jobs in the past. Here's what happens behind the scenes:
Put it differently, Predictions are like getting advice from thousands of people who've gone before you, condensed into a few smart suggestions to help you move forward with confidence.
Yes! With the Simulation feature, Jobography can help you chart a step-by-step journey from your current job to your dream job. Think of it like using a GPS for your career. Here's how it works:
We aggregate and harmonize data from a wide range of publicly available sources — including government databases, online job postings, and real-time labor market information — to power our proprietary datasets. This process ensures that all information about jobs and careers is standardized, consistent, and comparable across industries and geographies.
Our advanced machine learning models are trained on this comprehensive dataset to analyze and project individual career trajectories. These insights are personalized to each user's unique employment history, yet grounded in patterns drawn from hundreds of thousands of data points across the global workforce.
Following data harmonization, we refine our models through continuous learning — combining machine intelligence with user feedback, expert domain knowledge, and logic-based recommendation systems. This multi-layered approach enhances the transparency, explainability, and reliability of our predictions.