Data Scientist
Posted on:
December 12, 2025
Job description
About the Role
We are seeking a skilled Data Scientist to develop and implement advanced analytics and machine learning solutions that drive data-informed decision-making across the organisation. This role involves designing predictive models, optimising algorithms, and collaborating with cross-functional teams to deliver actionable insights for enterprise-scale applications.
Responsibilities
Key Responsibilities
- Data Analysis & Modelling: Develop and deploy statistical models and machine learning algorithms to solve complex business problems.
- Prototype Development: Build proof-of-concept apps to demonstrate new or state-of-the-art models and algorithms.
- Model Evaluation, Monitoring & Improvement: Implement processes for validating, testing, and monitoring models to ensure accuracy and reliability.
- Collaboration: Work closely with product, engineering, and business teams to translate requirements into data-driven solutions.
- Visualisation & Reporting: Create dashboards and reports to communicate insights effectively to stakeholders.
- Compliance & Governance: Ensure all data science activities adhere to organisational standards and regulatory requirements.
Job requirements
Requirements
- Australian Citizenship (mandatory for NV1 defence clearance eligibility).
- Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field.
- 3+ years of experience in data science or advanced analytics roles (including post-graduate study).
- Proficiency in Python, and experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Strong understanding of statistical modelling, predictive analytics, and data visualisation.
- Experience working with large datasets.
- Excellent problem-solving and communication skills, including the ability to present technical concepts to non-technical audiences.
Desirable
- Experience working with cloud platforms (AWS, GCP, or Azure).
- Experience with Java. Experience with React for fronted development.
- Familiarity with MLOps practices and version control (Git) is advantageous.
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