Andrea Jackson

Led Monash Health's Automation & Advanced Analytics function within the Business Intelligence team, managing a team of 3–6 specialists including Data Scientists, Automation Analysts, and Reporting Analysts, in a broader BI team of up to 23. Oversaw recruitment, performance reviews, project scoping and prioritisation, while driving improvements to project documentation, communication processes, and data product governance.

Key tools: SQL, Python, Power Automate, Power BI

Key achievements:

• Private Patient Conversion Prioritisation: Developed and deployed a model estimating financial benefit and urgency to support the Patient Liaison Team, directly aligning with Monash Health's strategic goal of financial stability; increased anticipated private funding by 8–10%.
• Established a centralised data product register for models, applications, and automations, improving transparency and lifecycle management.
• Advocated for the implementation of an Azure ML environment to enable scalable, secure advanced analytics capabilities.

Contributed to the establishment and growth of Ventia's Data Science & Advanced Analytics capability within the DNA team directly managing a team of 3–8 Data Scientists, Analysts, and Engineers in a broader data function of up to 20 people.. Oversaw recruitment, performance management, pipeline planning, data strategy, stakeholder engagement, and project governance, applying a modified Agile approach to delivery.

As part of my role I coordinated regular meetings bringing together 100-150 members of staff data & analytics components to their role or within their team across the enterprise, to facilitate knowledge sharing and promotion of successful initiatives that could be applied to other divisions.

Played a hands-on role in building the data platform, including setup of Azure RBAC and the Alex Solutions catalogue, and introduced a JIRA project and task tracking system to streamline workflow management and data governance.

Key tools: SQL, Python, Azure

Key achievements:

• Strategic Roadmap: Authored a comprehensive data and analytics roadmap, refining policies, procedures, and controls tailored to Ventia's diverse operations, enabling a scalable and robust data capability.
• Data Platform & Governance: Spearheaded the build-out of the data platform, establishing secure access controls and governance structures to support quality data capture and usage.
• Process Improvement: Redesigned on-site ‘start work' forms to capture richer data for compliance reporting, enhancing safety and regulatory tracking.
• Scheduling Optimisation: Developed predictive models to optimise scheduling for telecommunications engineering work, increasing appointment availability in high-density areas.
• IoT Expansion: Collaborated with a vendor to extend and enhance an IoT deployment, broadening its scope and improving tools for more informed operational decision-making.
• Drone Imaging for Power Line Inspections: Initiated the use of drone-based image detection to support power line inspections, enhancing efficiency and safety of asset monitoring.

Provided advisory, project management, and hands-on analytical services to Wilson AI on a contract basis, delivering tailored data science solutions using Python. Contributed as an independent consultant, applying technical expertise to support client objectives and deliver actionable insights.

Key tools: Python

Key achievements:

• Delivered end-to-end analytical and advisory work to support Wilson AI's data-driven projects and client deliverables.
• Managed project timelines and deliverables independently, ensuring high-quality outcomes in line with client expectations.

Led a team of 4 Data Scientists within Liberty Financial's Data & Consulting function, providing coaching and guidance to embed process discipline, clear prioritisation, and a strong commercial focus into all project delivery.

Introduced structured approaches to project prioritisation and management reporting, ensuring outcome-based practices and measurable value from data science initiatives.

Key tools: Snowflake

Key achievements:

• Established and embedded processes to prioritise work based on commercial impact, improving alignment between technical delivery and business outcomes.
• Enhanced management reporting to increase transparency and accountability for in-progress and delivered projects.
• Fostered a high-performance culture by coaching team members to apply a consistent commercial lens to data science solutions.

Managed a team of 5–8 Data Scientists, Graduates, and Data Engineers within a broader Analytics & Data Science function of up to 20 people. Acted as 2IC to the Head of Analytics & Data Science, partnering directly with vertical executives in Energy & Telco and later Health, attending daily stand-ups to communicate results and respond rapidly to business needs.

Responsible for recruitment, performance development, and change management to embed new model-driven processes across the business.

Proactively enhanced team efficiency by addressing administrative gaps and strengthening cross-team engagement.

Key tools: SQL, Python

Key achievements:

• Recommendation System: Consulted on the introduction of a machine learning–driven recommendation system, advising on design and implementation to improve customer experience and conversion.
• Model Scaling: Led the scaling of existing ML models, managing the overall program while contributing directly to hands-on development, ensuring robust, production-ready deployments aligned with business objectives.
• Business Partnership: Served as an embedded analytics partner to senior stakeholders, translating complex insights into actionable recommendations and supporting daily operational decisions.

Delivered predictive modelling and advanced analytics to support key business objectives within Sportsbet's Data Science team of 8–10. Worked closely with stakeholders across marketing, finance, and customer engagement to maximise ROI and optimise decision-making through robust statistical and machine learning solutions.

Key tools: SQL, Python, Amazon Redshift

Key achievements:

• Developed predictive models to maximise the return on investment of online marketing campaigns, driving targeted and efficient spend.
• Built financial forecasting models to support accurate budgeting and financial planning.
• Designed and implemented classification and regression models to deepen customer understanding and enable more effective, personalised customer interactions.

Held multiple roles of increasing responsibility across ANZ's retail risk, credit analytics, and decision strategy functions, managing teams of up to 20 and direct reports up to 6. Provided hands-on analytical leadership, governance oversight, and cross-functional project delivery, working closely with technology partners, SMEs, and senior stakeholders to deliver data solutions aligned with enterprise standards and strategic objectives.

Technical work across the model lifecycle including extensive experience in data extraction, cleansing, modelling, and scorecard development.

Key tools: SAS

Key achievements:

• Retail Risk Modelling: Led the Process & Migration Stream, collaborating with process improvement and change management SMEs to ensure fit-for-purpose solutions; designed and delivered data pipelines compliant with enterprise strategic data sourcing and platform architecture requirements.
• Decision Strategy & Governance: As Manager of Retail Decision Strategy, governed model usage for managing retail credit portfolios, optimised strategies to minimise credit losses to P&L, and ensured alignment between collections and credit cost management.
• NZ Simplification Project: Seconded as Program Manager to assess the impacts of rebranding and back-office simplification for ANZ's NZ retail customers, managing analysts and providing strategic analysis and expert advice to guide decision-making.
• Credit Analytics: Managed project design, data preparation, scorecard build and validation, and documentation
• People & Culture: Founded the Risk Infrastructure Charity Champions group and team Social Club, and actively contributed to communication, engagement, and fundraising committees to strengthen team culture and community impact.

Supported the development and validation of credit scorecards within NAB's Global Retail Credit team, using SAS to deliver robust statistical analyses and maintain model performance.

Set up and maintained an organised, efficient filing system for scorecard documentation, creating a central resource that improved knowledge sharing and accessibility for colleagues across the bank.

Key tools: SAS

Key achievements:

• Assisted in end-to-end scorecard builds and validations, ensuring high-quality models for retail credit risk management.
• Designed and maintained a centralised document repository for scorecard materials, streamlining access and improving team efficiency.