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Senior Data Scientist
Division: Australia Retail
About Us
At ANZ, we're shaping a world where people and communities thrive, driven by a common goal: to improve the financial wellbeing and sustainability of our millions of customers.
About the Role
As a Data Scientist in Personalization tribe, you’ll play a key role in helping to drive value and improve customer experiences in marketing. This role manages the tribe backlog, working closely with others to prioritise work, manage interdependencies and distil features to epics. TPLs define what success looks like for the tribe and then measure their progress against that. In some cases, this role will also manage a chapter of Product Owners.
Banking is changing and we’re changing with it, giving our people great opportunities to try new things, learn and grow. Whatever your role at ANZ, you’ll be building your future, while helping to build ours.
What will your day look like?
- Work with different data sources and analyse customer data to understand trends and provide insights, opportunities and recommendations using classic and advanced analytics techniques.
- Identify use cases for, and build, deploy, and productionize algorithmic and predictive models to improve marketing campaigns and personalize customer experiences.
- Proactively suggest ways to enhance targeted campaigns and personalized communications using advanced analytics techniques and data science assets.
- Meet and collaborate with stakeholders to understand their needs and requirements and provide analytical insights, recommendations and solutions.
- Utilising statistical and advanced analytics techniques to monitor different metrics and deliver data-driven insights and solutions.
What will you bring?
- At least 5 years of experience as a Data Scientist or in similar roles, with proficiency in tools such as SQL, Python, PySpark, and GCP.
- Experience in Machine Learning, Predictive Modeling, and strong knowledge of statistics and advanced analytics for solving business problems.
- Experience working with large and diverse datasets, ideally in a banking or marketing environment.
- Strong communication and storytelling skills to convey analytical insights and solutions to non-technical stakeholders.
- Ability to collaborate effectively with cross-functional teams, including members from different geographies.