Lead Data Scientists

Digital Business Division DBD are the custodians of the customer experience ensuring seamless, secure, and trusted interactions for agricultural trade and biosecurity. From permits, audits and certifications to declarations and compliance checks, our platforms and products are where industry and government connect. Our work is about more than technology. It's about trust. Our customers and staff trust that they can access simple reliable services that support them to undertake their role and compete in global markets. We are unifying and modernising our systems and seeking to build re-usable digital capabilities to give our customers a unified service experience; one place to get what they need from government, anytime, anywhere. By simplifying complexity, we enable industry to spend less time on paperwork and more time growing, producing and trading. Our purpose is to deliver digital and data services that make agricultural cross border trade and travel easier, safer, and stronger for Australia. Every member of our division –no matter our role or location –contributes to that mission.  Key duties and responsibilities Key duties and responsibilities Developing and creating and deploying advanced predictive and prescriptive analytical models specific to imported cargo in the biosecurity domain. This encompasses all aspects of design, development, implementation, deployment, testing and evaluation of model’s performance. Required skills and experience Demonstrated experience operating as a data scientist in data/analytics contexts, including stakeholder management, discovery, documentation of requirements, and translating business needs into implementable data solutions. Strong communication and facilitation skills, with the ability to build trust, run effective workshops, and work as a collaborative team member across business and technical stakeholders. Hands-on data engineering experience delivering pipelines and transformations, with strong SQL, Python and R and experience working with modern data platforms and orchestration patterns. Strong data science and modelling and warehousing capability (conceptual/logical/physical, dimensional modelling), and an understanding of how models enable trusted reporting and self-service analytics. Ability to rapidly learn new tools and delivery patterns; willingness to work within DAFF’s ecosystem (including Curator, Azure, DataBricks and Power BI) and become productive quickly. Experience implementing data quality controls (profiling, validation rules, reconciliation, exception handling) and producing clear documentation (data mapping, lineage, runbooks). Ability to drive delivery with limited supervision, including planning, prioritisation, risk/issue management and coordination across dependencies (light project delivery support). Baseline security clearance (mandatory) and demonstrated commitment to handling sensitive information appropriately. Experience in AI modelling and implementation into production of AI use cases and products. Criteria The buyer has specified that each candidate must provide a response to each criterion. Each response is limited to 3000 characters. Essential criteria Weighting 1. Proven experience in creating and deploying advanced predictive and prescriptive analytical models specific to business entity resolution in the biosecurity domain. This encompasses the design, development, implementation, deployment, testing, and evaluation of data mining processes, models, and products, with a focus on their application in entity resolution. Proficiency in deploying these solutions within a production environment is also essential. Weighting: 35% 2. A successful candidate must demonstrate a strong ability to work collaboratively with diverse teams to develop and maintain robust stakeholder relationships. Effective collaboration is essential for aligning project objectives with business goals, ensuring that the entity resolution processes meet organizational needs. The candidate should also have the capability to support informed decision-making and influence others to achieve project and business milestones. Weighting: 35% 3. Demonstrated experience in providing accurate, timely and appropriate advice and updates to clients and stakeholders. This includes presenting sophisticated analytical products to non-technical audience and senior executive. Weighting: 30% Desirable criteria 1. Experience working in a DevOps environment Experience in conducting machine learning work in a cloud environment with Markov random fields prediction Experience working with DAWE's data and in DAWE's technical environment Experience in working with DAWE’s business entities and business processes Opportunity summary Sellers can submit Up to 3 candidates Number of sellers invited Between 5 and 10 Number of candidates submitted Fewer than 10 Send us feedback About Accessibility Privacy Terms of use Disclaimer and copyright An initiative of the Digital Transformation Agency The Australian Government acknowledges the Traditional Owners of Country throughout Australia and acknowledges their continuing connection to land, waters and community. We pay our respects to the people, the cultures and the Elders past and present. © Commonwealth of Australia