Data Scientist - Machine Learning and Generative AI - Full Time

Data Scientist - Machine Learning and Generative AI - Full Time

Job Type: Permanent position | Full time position

Job Description

DATA & KNOWLEDGE ENTERPRISE PTY LTD 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 pr...