Job Title: Data ScientistLocation: Australia (On-site / Hybrid / Remote )Job Description:We are seeking a highly analytical Data Scientist to join our team and help transform raw data into valuable insights. In this role, you will work closely with cross-functional teams to build predictive models, perform statistical analysis, and support data-driven decision-making across the organisation. You will play a key part in developing scalable solutions that improve business performance and strategic outcomes.Key Responsibilities:Collect, clean, and analyse large datasets from multiple internal and external sources.Build predictive models and machine-learning algorithms to support business initiatives.Develop dashboards, reports, and visualisations to communicate insights clearly.Conduct A/B tests, statistical analyses, and experimental designs.Identify trends, patterns, and actionable insights to support strategic planning.Work with engineering teams to deploy, monitor, and optimise ML models.Collaborate with business units to translate needs into data solutions.Ensure model accuracy, data quality, and scalable pipeline performance.Required Qualifications:Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.Strong experience with Python or R for data analysis and modelling.Hands-on experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).Proficiency in SQL and data manipulation tools.Familiarity with data visualisation tools (Tableau, Power BI, or similar).Solid understanding of statistical methods, predictive modelling, and experimental design.Ability to explain technical concepts to non-technical stakeholders.Preferred Skills (Optional):Experience with cloud platforms (AWS, GCP, Azure).Knowledge of big data tools (Spark, Hadoop).Familiarity with MLOps or model deployment workflows.Experience in building end-to-end data pipelines.What We Offer:Flexible working arrangements (remote/hybrid options).Opportunity to work with modern data tech stacks and real business problems.Collaborative and data-driven work culture.Growth opportunities, training, and career development.
