Data Scientist

• Design and deliver models, analytics, and insight frameworks for Finance and Corporate teams
• Lead work on forecasting, planning, and performance management
• Build solutions directly while mentoring analysts and data scientists
• Connect with data teams to maintain metrics and definitions across the company

Senior Data Scientist, Finance

• Design and deliver models, analytics, and insight frameworks for faster decision-making within Finance and G&A teams
• Lead forecasting, planning, and performance management efforts, embedding models in key operational cycles
• Build solutions independently as part of a high-impact team
• Mentor analysts and data scientists across G&A to enhance AI and advanced analytics application
• Collaborate with teams to create usable models and dashboards from complex data

• Collect, clean, and preprocess structured and unstructured data from multiple sources.
• Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
• Develop and test predictive models using statistical and machine learning techniques.
• Assist in building data pipelines for data collection, transformation, and validation.
• Create dashboards and visualisations using Power BI, Tableau, or Python libraries to communicate insights.
• Write SQL queries to extract, manipulate, and analyse large datasets.
• Support feature engineering and model optimisation to improve prediction accuracy.
• Evaluate model performance using appropriate metrics and validation techniques.
• Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions.
• Prepare reports and presentations summarising analytical findings and recommendations.
• Document methodologies, code, and model assumptions to ensure reproducibility.
• Assist in automating repetitive data processing and reporting tasks using Python or R.
• Conduct research on emerging AI, machine learning, and data science techniques.
• Ensure data quality, integrity, and compliance with organisational data governance standards.
• Participate in team meetings, code reviews, and knowledge-sharing sessions.

Data Scientist Intern

• Design, build, and validate predictive models (e.g. lead scoring, propensity modelling, forecasting, risk prediction) that inform operational and strategic decisions.
• Develop and deploy generative AI solutions, including LLM-powered agents, retrieval-augmented generation (RAG) pipelines, and prompt engineering workflows to automate and enhance business processes.
• Translate business problems into well-scoped analytical and modelling projects, working with stakeholders to define success criteria and measurable outcomes.
• Perform feature engineering, model selection, hyperparameter tuning, and rigorous evaluation using appropriate statistical and ML techniques.
• Productionise models into scalable, maintainable pipelines, collaborating with data engineering to integrate outputs into downstream systems (e.g. CRM, BI tools, operational dashboards).
• Monitor model performance post-deployment, manage model drift, and implement retraining strategies.
• Communicate findings and model outputs to non-technical stakeholders through clear visualisations, written summaries, and presentations.
• Stay current with developments in applied ML and generative AI, and contribute to the team’s knowledge-sharing and capability-building efforts.
• Provide guidance, direction, and oversight to one direct report within the Data, Insights & AI team.

• Support the development of predictive models across the student lifecycle, including lead scoring, conversion propensity, retention risk, and demand forecasting.
• Assist in building and evaluating generative AI solutions, such as LLM-powered agents, prompt engineering workflows, and retrieval-augmented generation (RAG) pipelines.
• Perform exploratory data analysis, feature engineering, and data wrangling to prepare datasets for modelling.
• Write clean, well-documented Python code for analysis and model development.
• Help productionise models by supporting pipeline development, testing, and integration with downstream systems.
• Prepare visualisations, summaries, and presentations that communicate analytical findings and model outputs to non-technical stakeholders.
• Contribute to the team’s knowledge base by documenting methods, sharing learnings, and participating in code reviews.
• Proactively develop your own skills through structured learning, certifications, and hands-on experimentation.

Associate Data Scientist

• Help uplift data governance across Australian Ethical by establishing a practical framework
• Establish and embed data governance policies, standards, controls and practical ways of working across the business
• Define data ownership, stewardship and accountability across key business domains
• Identify Critical Data Elements and support risk assessments with Data Owners
• Set data quality standards and monitoring processes
• Design issue management processes to support timely detection and remediation of data issues
• Partner with Internal stakeholders and external vendors to understand data flows, risks and business requirements
• Support governance forums and working groups to drive adoption and accountability
• Deliver training to help teams understand and apply data governance policies, standards and controls

Data Governance Lead

• Join HUB24 as a Product Manager within our Data Products team, where you'll play a key role in shaping and delivering innovative data-driven solutions across the HUB24 ecosystem.
• Support the delivery of HUB24’s Data Products strategy and roadmap, aligned with business objectives.
• Identify opportunities to enhance data capabilities and create value for customers and stakeholders.
• Work with customers and internal teams to understand needs and translate them into product outcomes.
• Help drive trusted, reliable and user-friendly data solutions.
• Contribute to the development and execution of the Data Products roadmap.
• Support prioritisation decisions based on customer value, business impact and strategic objectives.
• Work closely with engineering and data teams to deliver product initiatives from discovery through to release.
• Monitor product performance and incorporate feedback to drive continuous improvement.
• Help translate data capabilities into commercially valuable products and solutions.
• Track product adoption, usage and performance metrics to inform decision-making.
• Partner with stakeholders across the business to align product initiatives with broader organisational goals.
• Collaborate with engineering and data teams to deliver scalable, market-leading data products.
• Develop an understanding of modern data platforms, architecture and emerging technologies.
• Leverage product management tools, analytics and AI-driven insights to support product development.
• Stay informed on industry trends and opportunities to enhance HUB24’s data product offering.

Product Manager, Data Products

• Lead Audinate's Data and Insights function in line with commercial priorities
• Partner with leaders across Sales, Marketing, Finance, Product, and Strategy to surface evidence that helps make decisions that drive growth
• Establish a recurring cadence of reporting that the ELT and Board use for planning
• Make foundational decisions on data warehouse, modelling layer, and visualisation tooling
• Lead a small team with a product-team operating mode
• Establish governance and quality standards across datasets used by the business
• Grow strong collaborative partnerships with functions that own datasets
• Lift the analytical capability of the business
• Carry analysis through to the decisions it informs

Senior Manager, Data and Insights

• Leading investment risk analysis across whole-of-fund, strategy and portfolio levels.
• Proactively partnering with our portfolio managers and investment team leadership to identify, assess and manage investment risks and opportunities.
• Developing and enhancing investment risk frameworks, analytics and reporting.
• Driving understanding of market, liquidity and sustainability-related risks.
• Building a strong investment risk culture through thought leadership and trusted advice.

Head of Investment Risk, Analytics

• Lead PO data cleansing and validation activities across MSD, including closing redundant or inactive POs and correcting data anomalies
• Assess migration readiness by validating Period of Performance (POP) data and determining which POs and PO lines will transition to Costpoint
• Support data mapping and preparation activities to enable a successful ERP migration
• Define and implement standardised PO structures and develop templates to support consistent procurement practices
• Partner with Operational Units to align existing POs with agreed standards and business rules
• Support the implementation of cyber security questionnaire requirements within procurement processes
• Coordinate cross-functional stakeholder engagement to validate procurement data and support broader cleansing initiatives
• Assist with procurement-related security role mapping and process alignment between MSD and Costpoint
• Provide guidance and training to business users on Costpoint P2P processes and improved procurement practices

Data Scientist jobs in Australia

See all jobs on JobTailor

Senior Data Scientist, Finance

Senior Data Scientist, Finance

Data Scientist Intern

Data Scientist

Associate Data Scientist

Data Governance Lead

Product Manager, Data Products

Senior Manager, Data and Insights

Head of Investment Risk, Analytics

Procurement and P2P Data Lead