Data Scientist - Analytics

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