Data Scientist

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

The Data Scientist for Financial Wellbeing Modelling will develop predictive models to measure customer financial wellbeing, using data analysis to generate actionable insights. These wellbeing scores will be integrated into customer engagement strategies in retail and digital platforms. The role involves understanding retail data and customer behaviour, and building algorithms to assess financial wellbeing. Collaboration with behavioural scientists is key to incorporating psychological and demographic factors into the models.

Working with a team of data scientists, engineers, and analysts, the Data Scientist will apply analytical skills to a wide range of data to create customer-centric solutions. The role also involves communicating insights through data visualization and storytelling, supporting data-driven decision-making across the organization.

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.

Role Location: Manyata Tech Park, Bengaluru
Role Type: Permanent, Fulltime 

What will your day look like?

• Use large datasets to identify insights, design sophisticated algorithms, and drive strategic solutions that have a measurable impact on the organization, improving business processes and automating decisions. 
• Advocate for the adoption of data-driven, fact-based approaches throughout the bank, ensuring that your models and insights influence decision-making at all levels. 
• Design, build, and deploy models tailored to customers, products, and business channels, continuously evaluating their performance to maintain relevance and effectiveness. 
• Gather and synthesize data from diverse sources to provide insights that optimize key business decisions, such as pricing strategies, campaigns, and product propositions. 
• Drive the development and implementation of cutting-edge data science capabilities, leading the creation of tools and methodologies that profile customer segments and optimize business performance, while supporting data platforms and decision delivery tools. 

What will you bring?

• A solid understanding of the banking sector, including knowledge of products, services, channels, and the associated data structures and dynamics.  
• Deep knowledge of core statistical concepts such as probability, hypothesis testing, regression, and analysis of variance. Hands-on experience with predictive modeling, pattern recognition, clustering, and both supervised and unsupervised learning algorithms.  
• Expertise in leading comprehensive EDA exercises to uncover key patterns, trends, and anomalies within complex datasets, applying various statistical techniques and visualization tools to generate actionable insights.  
• A minimum of 3-5 years of experience in predictive modeling, with a strong focus on financial services or digital banking preferred. Proficiency in building models that directly impact business decision-making.  
• Solid grounding and hands-on knowledge in SQL, Python and PySpark. 
• Proven expertise in utilizing Google Cloud Platform (GCP) to build scalable data pipelines, deploy machine learning models, and manage large datasets. Proficient in cloud-native GCP tools such as BigQuery, DataProc, Cloud Storage, and AI Platform to efficiently develop, train, and deploy machine learning models at scale. 
• Intellectually curious, creative, and diligent - you enjoy thinking about the business as much as the data! 
• Strong ability to translate technical data insights into actionable business strategies and recommendations, ensuring alignment with organizational goals  
• Strong ability to effectively communicate complex data insights to both technical and non-technical stakeholders. Adept at storytelling with data and delivering compelling presentations. 
• Proven ability to work in a fast-paced, dynamic environment, managing multiple priorities and ensuring high-quality results in a timely manner. 
• A degree in Economics, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. 

You’re not expected to have 100% of these skills. At ANZ a growth mindset is at the heart of our culture, so if you have most of these things in your toolbox, we’d love to hear from you. 

Job Posting End Date

4th Dec 2024, 11.59pm, (Melbourne Australia)