Data Scientist

Sharp & Carter; Brisbane; Presencial; AUD 95.000 - 130.000; Jornada completa

Descripción de la vacante

Sharp & Carter is seeking an experienced Data Scientist to contribute to a major Data & Analytics uplift program in Queensland. You will work with complex data to develop ML models, analytics and decision-support capabilities that translate data into measurable business outcomes.

The role emphasises predictive modelling, risk identification and deploying reliable, production-ready AI/ML solutions, collaborating with data professionals and business stakeholders to improve decision-making and

Formación

• Experience applying ML to complex datasets with business outcomes.
• Strong statistical and predictive modelling capabilities.
• Practical experience with Python, SQL and Azure Databricks.
• Experience deploying AI/ML solutions through CI/CD processes.
• Exposure to NLP and text analytics is advantageous.

Responsabilidades

• Developing and evaluating predictive models using classification, regression, time-series analysis and other statistical techniques.
• Applying machine learning to large, complex datasets to identify trends, anomalies and opportunities for intervention.
• Using Python, SQL and Azure Databricks to develop analytical and ML solutions.
• Supporting the deployment of AI/ML solutions through CI/CD processes.
• Monitoring and optimising production solutions for performance, cost, latency and reliability.
• Exploring NLP and text analytics techniques to extract insights from unstructured documentation.
• Translating analytical findings into actionable insights for business stakeholders.

Conocimientos

Machine learning

Predictive modelling

Python

SQL

Azure Databricks

CI/CD

NLP

Educación

Data Science degree

Statistics degree

Mathematics degree

Herramientas

Azure Databricks

Descripción del empleo

Data Scientist | Machine Learning & Predictive Analytics

6 month Contract opportunity

Apply data science to meaningful business challenges

An exciting opportunity is available for an experienced Data Scientist to contribute to a major Data & Analytics uplift program within a large Queensland organisation.

Working across complex structured datasets and unstructured documentation, you will develop machine learning models, advanced analytics and decision-support capabilities that translate data into measurable business outcomes.

This is an opportunity to apply your technical expertise to practical challenges, with a focus on predictive modelling, risk identification and the development of reliable, production-ready AI/ML solutions.

The opportunity

You will work with data professionals, subject matter experts and business stakeholders to develop analytical solutions that improve decision-making, identify emerging patterns and support more effective operational outcomes.

• Developing and evaluating predictive models using classification, regression, time-series analysis and other statistical techniques.
• Applying machine learning to large, complex datasets to identify trends, anomalies and opportunities for intervention.
• Using Python, SQL and Azure Databricks to develop analytical and ML solutions.
• Supporting the deployment of AI/ML solutions through CI/CD processes.
• Monitoring and optimising production solutions for performance, cost, latency and reliability.
• Exploring NLP and text analytics techniques to extract insights from unstructured documentation.
• Translating analytical findings into actionable insights for business stakeholders.

About you

You will bring:

• Demonstrated experience applying machine learning to complex datasets and delivering measurable business outcomes.
• Strong statistical and predictive modelling capabilities.
• Practical experience with Python, SQL and Azure Databricks.
• Experience deploying AI/ML solutions through CI/CD processes.
• An understanding of production model monitoring, performance optimisation and reliability.

Experience with NLP, text classification, topic modelling or large-scale document analytics will be highly regarded.

Experience in insurance, government or another regulated environment is also advantageous.

A degree in Data Science, Statistics, Mathematics or a related discipline is desirable.