Optimise a complex forecasting model in R beyond MVP within a mature Git-driven production environment | ASAP–31/12/26 + 12

This role is within a large federal social policy agency supporting one of the a significant reforms currently underway to this sector.

The team provides modelling, forecasting, and analytical support to inform funding, pricing, regulatory, and policy decisions.

Their work helps policy and program areas understand provider viability, sector performance, reform impacts, and long-term sustainability across a highly interconnected system.

The Opportunity

This is an opportunity to take a genuinely complex production forecasting model in R and help evolve it into a mature, scalable modelling product with direct influence on major reform and investment decisions.

You’ll join a highly technical team of data scientist, data modelers and econometricians operating with strong coding practices, modern modelling workflows, and a long-term roadmap to significantly expand the scope, sophistication, and operational maturity of the platform.

- Complex forecasting and scenario modelling with real policy and market impact
- Mature technical culture with Git workflows, R package development, CI/CD and evolving MLOps capability
- Take an MVP model to the next level through optimisation, QA uplift, ETL enhancement, validation checking and improved analytics outputs
- Significant growth planned across new cohorts, datasets, modelling streams and broader forecasting capability

The Role

You’ll work closely with a small technical team to enhance and operationalise complex forecasting and scenario models built in R. This work includes improving and optimising the current ETL process & pipelines (with the data primarily sourced from Oracle)





Responsibilities include:

- Enhance and maintain production-level forecasting and estimation models in R
- Improve model outputs, analytics, and stakeholder usability
- Develop reusable, maintainable, and production-ready R code and packages
- Improve ETL workflows, data quality controls, validation, and QA processes
- Design and enhance reporting and visualisation capability in R Shiny
- Contribute to broader engineering uplift across Git workflows, testing, CI/CD, and MLOps capability

The Ideal Person

This role will suit a Data Scientist, Modeller, Actuary, or similar quantitative professional with advanced R skills who enjoys technically complex modelling problems and improving the quality, scalability, and robustness of existing systems. Your experience will likely including roles where data and policy intersect which has given you the skills to translating complex datasets and assumptions into products that support real-world strategic and economic decision-making.

From a technical perspective you will have Advanced R (& SQL) in a genuine production setting, including experience with Git/version control, reusable and scalable coding practices, R package development, testing frameworks, and building maintainable codebases.

Due to the nature of the work and data sets Australian Citizenship with a Baseline (or above) Clearance is mandatory

Salary / Rate

This role is being offered as a full-time EL1 equivalent rate contract

ASAP start through to 31/12/26 with 2x 6-month extension options

Be careful - Don’t provide your bank or credit card details when applying for jobs. Don't transfer any money or complete suspicious online surveys. If you see something suspicious, report this job ad .

#J-18808-Ljbffr

📌 Data Scientist (Canberra)
🏢 HorizonOne Recruitment
📍 Canberra