Job Description

About the Opportunity

DXC Technology is pursuing a large-scale Government Data & Analytics Transformation program, commencing with a discovery and architecture definition phase before progressing into implementation.

The program will assess and define a future-state solution to support secure data ingestion and integration across Government, rules and analytics, explainable AI, workflow automation and human-led decision-making across classified LOW and HIGH environments.

We are seeking experienced Data Scientists and Machine Learning Specialists to support the design, development and implementation of advanced analytics and AI capabilities across the program.

The successful candidates will work with data architects, data engineers, solution architects, business analysts and other technical specialists to identify opportunities for applying data science and machine learning to complex business problems.

We are particularly interested in candidates who can translate business requirements into practical analytical and AI solutions, with an understanding of explainability, responsible AI, model performance and the importance of human oversight in decision-making.

Key Responsibilities

• Analyse complex business problems and identify opportunities to apply data science, advanced analytics and machine learning.
• Work with business stakeholders and technical teams to understand requirements and translate them into analytical use cases.
• Explore, prepare and analyse large and complex datasets from multiple sources.
• Develop, train, test and validate statistical models and machine learning algorithms.
• Design and implement predictive, classification, clustering, anomaly detection and other analytical models as appropriate.
• Develop AI-enabled capabilities to support insights, operational decision-making and business processes.
• Apply explainable AI techniques to ensure model outputs, recommendations and predictions can be understood and interpreted by users.
• Evaluate model accuracy, performance, reliability, bias and limitations.
• Work with data engineers to prepare datasets, develop pipelines and operationalise analytical models.
• Collaborate with solution architects and engineering teams to integrate models into enterprise platforms and workflows.
• Develop proof-of-concepts and prototypes to demonstrate the feasibility and value of proposed AI and analytics solutions.
• Support the transition of models from experimentation and development into production environments.
• Establish model monitoring, validation and performance measurement approaches.
• Document methodologies, assumptions, model outputs, limitations and technical recommendations.
• Ensure AI and machine learning solutions align with security, privacy, governance and responsible AI requirements.
• Contribute to the evaluation of COTS and Government-proven analytics and AI platforms.

Essential Experience & Skills

• Demonstrated experience as a Data Scientist, Machine Learning Engineer, Applied AI Specialist or similar.
• Strong experience applying statistical analysis, data science and machine learning techniques to complex business problems.
• Experience developing, training, evaluating and validating machine learning models.
• Strong programming skills, particularly Python and relevant data science libraries.
• Experience working with large, complex datasets and performing data exploration, preparation and feature engineering.
• Strong understanding of statistical methods, predictive modelling and model evaluation techniques.
• Experience with machine learning frameworks and libraries such as Scikit-learn, TensorFlow, PyTorch or similar.
• Understanding of model deployment, integration and the practical challenges of operationalising machine learning solutions.
• Experience communicating technical findings and analytical insights to both technical and non-technical stakeholders.
• Ability to translate business requirements into practical data science and machine learning solutions.

Desirable Experience

• Experience with enterprise data and AI platforms such as Databricks, Snowflake or Palantir Foundry.
• Experience developing solutions involving explainable AI (XAI), interpretable models and transparent decision-support capabilities.
• Exposure to generative AI, large language models (LLMs), natural language processing or retrieval-augmented generation (RAG).
• Experience with predictive analytics, anomaly detection, optimisation or intelligent automation.
• Familiarity with MLOps practices, including model deployment, monitoring, versioning and lifecycle management.
• Experience with cloud-based AI and machine learning services across Azure, AWS or Google Cloud Platform.
• Experience integrating analytical models into enterprise applications, workflow platforms or decision-support systems.
• Exposure to rules engines and workflow platforms such as Pega or Appian.
• Understanding of responsible AI, model governance, bias assessment, data privacy and ethical AI principles.
• Experience working with sensitive, regulated or classified data environments.
• Experience delivering solutions within Australian Government, Defence or National Security environments.
• Understanding of secure, on-premises, hybrid, cloud or air-gapped deployment environments.
• Relevant qualifications in Data Science, Computer Science, Statistics, Mathematics, Artificial Intelligence or a related discipline.

Location & Engagement

• Canberra-based roles, with on-site attendance preferred during the initial discovery and architecture definition phase.
• Technical LOW elements (PROTECTED) may also open opportunities in Zone 2 facilities in Sydney and Adelaide, subject to project requirements.
• Client-facing and business engagement roles are expected to be Canberra-based.
• Permanent and contracting opportunities may be considered.
• Security clearance requirements will be subject to project requirements and access to the relevant environment.
• The successful candidate will have an active NV2 clearance with a preference for TSPV.