Data Scientist - Analytics / ML

Melbourne / Sydney

$1100-1400 a day

12 month contract

Overview

We are working with a leading Financial Services client on a new role in their Data team. This role sits within a growing analytics function focused on supporting a direct-to-consumer business. The team is responsible for enabling better day-to-day decision-making through data, improving performance, and delivering actionable insights across the organisation.

You will work at the intersection of data science, analytics, and business strategy partnering closely with teams such as marketing and digital to translate data into meaningful outcomes.

Key Responsibilities

• Design and deliver machine learning models to solve business problems, with an initial focus on customer segmentation and clustering
• Explore and validate multiple data sources to identify opportunities for insight generation
• Translate business challenges into analytical frameworks and data science solutions
• Build, test, and deploy models using tools such as Python, SQL, and Databricks
• Develop reporting and visualisations to communicate insights to both technical and non-technical stakeholders
• Partner with internal teams (e.g. marketing, digital) to guide targeting, performance optimisation, and decision-making
• Contribute to the development of scalable data science capabilities and best practices
• Monitor and track model performance, ensuring solutions are production-ready and continuously improved
• Support migration and transformation of legacy analytics processes into modern data environments
• Clearly explain methodologies, outputs, and impact of models to a range of stakeholders

What You’ll Be Working On

• Customer segmentation projects using clustering techniques
• Exploratory data analysis to assess and validate available data
• End-to-end model development: from discovery → build → production → monitoring
• Enabling broader business use cases through incremental data science projects
• Supporting the evolution of the organisation’s analytics and machine learning capability

Skills & Experience

Essential:

• Strong experience with Python & SQL
• Hands-on experience building and deploying machine learning models
• Ability to work across the full data science lifecycle
• Experience working with large and complex datasets
• Strong communication skills—ability to explain technical concepts to non-technical audiences
• Experience working in collaborative, cross-functional environments

Desirable:

• Experience with Databricks or similar cloud-based data platforms
• Familiarity with BI/reporting tools and data visualisation
• Experience in customer analytics, marketing analytics, or digital analytics
• Understanding of clustering, segmentation, and other unsupervised learning techniques
• Exposure to agile delivery environments