DATA & KNOWLEDGE ENTERPRISE PTY LTD is seeking a full-time Data Scientist to design, develop, evaluate, deploy and improve machine learning, statistical modelling and AI-enabled solutions for enterprise clients.

The role applies analytical techniques and scientific procedures to structured and unstructured datasets, using statistical models, algorithms, machine learning frameworks, generative AI, and cloud-based data platforms to support strategic planning, operational analysis, and business decision-making.

The role has a particular focus on natural-language analytics, generative AI, cloud-based data platforms, and production data science workflows. This includes data preparation, model development, model evaluation, analytical workflow design, deployment support, monitoring, and communication of reliable business-facing insights.

Benefits

The annual salary for this full-time position is $95,000 – $105,000 + Superannuation

Task & responsibilities

Collect, clean, validate, transform, and analyse structured and unstructured datasets to identify patterns, improve data quality, and generate business insights.
Apply statistical modelling, predictive modelling, machine learning, and AI techniques to complex business datasets.
Develop, test, evaluate, deploy, monitor, and improve machine learning models, statistical models, LLM-enabled workflows, and AI-driven analytical outputs.
Design and implement data preparation, feature engineering, validation, and metadata workflows that support data science and AI-enabled analytics.
Write, validate, and optimise SQL queries for structured data analysis, model inputs, and reliable analytical outputs.
Develop Python-based analytical workflows, services, and APIs to operationalise statistical models, machine learning models, and AI-enabled outputs.
Design and improve natural-language data access workflows, including text-to-SQL, query validation, structured response generation, and interpretation of query results.
Work with retrieval-augmented generation, semantic search, vector embeddings, and graph-based retrieval where relevant to structured and unstructured data access.
Use cloud-based data platforms such as Microsoft Azure, Databricks, Snowflake, or similar platforms to support data science workflows and analytical products.
Apply reproducible data science and MLOps practices, including version control, experiment tracking, model monitoring, testing, documentation, and structured release practices.
Generate tabular outputs, automated reporting, visualisations, dashboards, summary statistics, and narrative insights for business stakeholders.
Collaborate with product, engineering, and business stakeholders to refine requirements, communicate technical outcomes, and deliver practical data-driven solutions.
Maintain appropriate standards of data governance, privacy, security, access control, responsible AI use, documentation, and reproducibility.

Essential Skills

Advanced Python skills for data science, statistical modelling, machine learning, analytical automation, and AI-enabled analytical workflows.
Strong SQL skills and experience preparing, validating, analysing, and interpreting structured datasets.
Strong capability in statistical modelling, predictive modelling, machine learning, model evaluation, data mining, and data quality assessment.
Experience with natural-language data access, text-to-SQL, SQL validation, retrieval-augmented generation (RAG), semantic search, embeddings, and LLM integration for analytical use cases.
Experience with cloud-based data platforms such as Microsoft Azure, Databricks, Snowflake, or similar platforms for data science workflows, model development, and analytical products.
Experience applying version control, CI/CD, Azure DevOps, Docker, and cloud deployment processes to support reproducible data science, machine learning and AI-enabled solutions.
Working knowledge of graph data technologies and query languages, including Neo4j, Cypher, knowledge graphs, and graph-based retrieval, including GraphRAG, where relevant to advanced data representation and semantic retrieval.
Ability to translate business problems into reliable, explainable, and scalable data-driven solutions.
Ability to communicate model outputs, analytical findings, visualisations, and narrative insights clearly to technical and non-technical stakeholders.
Understanding of data governance, privacy, security, access controls, reproducibility, documentation, responsible AI practices, and production monitoring.

Qualification & experience

A bachelor's degree or higher in a relevant quantitative discipline, such as Data Science, Mathematics, Statistics, Computer Science, or a closely related field.
At least one year of relevant experience in data science, statistical modelling, machine learning, applied AI, data analytics, or production data science workflows.
Experience working with cloud-based data platforms such as Microsoft Azure, Databricks, Snowflake, or similar platforms.

About Company

DATA & KNOWLEDGE ENTERPRISE PTY LTD is a specialist data science and technology company delivering data science, machine learning, and applied AI solutions for enterprise clients. We combine statistical modelling, machine learning, database technologies, and cloud-based data platforms to build scalable, secure, and business-focused analytical products.

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