Data Scientist, IND BLR, Grp 4.4

Job description

About The Role


Role Location - RMZ Ecoworld, Bangalore

Role Type - FTE, Perm, 4.4

At ANZ, our purpose is to shape a world where people and communities thrive. We’re making this happen by improving our customers’ financial wellbeing so they can achieve incredible things – be it buying their home, building a business, or saving for things big or small. ANZ is committed to leading people to better financial behaviours through use of data, insights and practical tools.

Understanding how our customers make financial choices in different contexts is essential for us to design products, services and experiences that improve their financial wellbeing, and fulfill our purpose.

The Data Scientist role for Financial Wellbeing Modelling will build predictive models to measure Customer Financial Wellbeing. The Financial Wellbeing scores will feed into various Customer engagement strategies in Retail and be embedded in the digital ecosystem for customers. The role will involve understanding the retail data and customer landscape and building suitable algorithms to measure financial wellbeing.

The incumbent will work closely with behavioural scientists within the Research, Development & Financial Wellbeing team, in order to embed behavioural aspects into the scores along with customer demographic and banking attributes.

As a Data Scientist, you will be working with a team of data scientists, Data Engineers and Data Analysts within the team as well as interacting with the broader Data community while building out the predictive and descriptive models. You will work hard to apply analytical skills to a broad range of data points to develop customer centric solutions. You will be communicating insights and models through impactful data visualisation and storytelling. With data and analytics at the heart of everything you do, you uncover insights and enable data driven decision making.

What Will Your Day Look Like

  • Address and solve complex business issues using large amounts of data.
  • Develop advanced algorithms that transform key business processes and automate banker decisions and activities
  • Implement a fact-based culture throughout the bank.
  • Continuous generation, monitoring, presenting and conducting of 'fact-based' analysis and models to use at any time for the development and improvement of relevant and innovative propositions
  • Design, build, deploy, monitor and assess relevant models for customers, clients, products and channels
  • Develop tools and methods to scientifically profile customers and customer segments, products and channels and associated costs, revenues, risks and opportunities
  • Source data from a variety of sources to combine, synthesise and analyse to support campaigns, pricing, propositions and other decisions
  • Initiate, design and implement innovative capabilities in the field of data science
  • Support key data platforms and/or tools to support decision delivery to key stakeholders (e.g. frontline, other tribes)
  • Lead, optimise, design and execute business interventions (customers and operational) to uplift customer engagement and business performance

What will you bring?

  • Strong communication and presentation skills
  • Good understanding of the Banking system and products, service, channels
  • Strong customer lens and affinity
  • Solid understanding of predictive modelling, pattern recognition, clustering, supervised and unsupervised learning algorithms
  • Work experience in the predictive modelling space for 3 to 6 years- Financial services/Digital Banking experience preferred though not mandatory
  • Proven experience in applied probability and statistics
  • Exposure to Digital Banking products/ processes is a plus
  • Hands-on knowledge and experience with tools and techniques for analysis, data manipulation and presentation (e.g. SAS, SQL, Python, Tableau, VBA, QlikView BI)
  • Experience in using open-source technologies for Data Science, specifically Python/R and key supporting packages/libraries and development environments
  • Analytical and inquisitive mindset to continuously improve the level of decisions automated
  • Strong ability to translate data insights into practical business recommendations
  • Strong statistical modelling and data management skills
  • Ability to effectively communicate to all stakeholders (technical and non-technical)

So, why join us?

There’s something special about being part of ANZ. From the moment you join us, you’re part of a team working towards a common goal: improving the financial wellbeing and sustainability of our millions of customers. And that’s big.

But it’s not just our customers who will feel your impact. You’ll feel it too. Because at ANZ, you’ll have the resources and community you need to take the next big step in your career, towards even bigger things in the future.

We offer a range of benefits tailored to the countries in which we operate to provide all our people:

  • Health and wellbeing programs
  • Discounts on selected products and services (from ANZ and beyond)
  • Flexible working arrangements, lifestyle leave and career breaks

You’ll also enjoy working in a diverse and inclusive workplace where the different backgrounds, perspectives and life experiences of our people are celebrated. We encourage you to talk to us about any adjustments you may require to our recruitment process or the role itself. If you are a candidate with a disability, let us know how we can provide you with additional support.

To find out more about working at ANZ or to view other opportunities visit

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