Chapter Lead

Organization:

At CommBank, we never lose sight of the role we play in other people's financial wellbeing. Our focus is to help people and businesses move forward to progress. To make the right financial decisions and achieve their dreams, targets, and aspirations. Regardless of where you work within our organisation, your initiative, talent, ideas, and energy all contribute to the impact that we can make with our work. Together we can achieve great things.

Job Title: Chapter Lead CDAO Decision Science Tech

Location: Bangalore

Business & Team:

Retail Banking Services (RBS) is the public face of CommBank, delivering a seamless banking experience for the future, to more than 10 million individuals and small businesses. We offer market-leading products and services, supported by some of the world's best systems and processes.

Impact & contribution:

As a Chapter Lead CDAO Decision Science, you will play a key role in the design, development, and deployment of state-of-the-art AI models in different areas in Retail Banking. In this role you will lead and mentor a team of talented data scientists to deliver high quality solutions leveraging machine learning, statistical modelling, and generative AI. You will also be supporting the uplift of AI capability across the group, empowering teams to deliver best outcomes for our customers and business. This role involves close collaboration with stakeholders, product owners, engineers, and other teams to develop and implement best in class AI solutions supporting group strategy.

Roles & Responsibilities:

You will be responsible for the development and management of key modelling assets within the team, with an objective to foster a team vision and approach that utilises state of the art data science and statistical techniques. You will be expected to drive higher quality/ efficient use of data through continuous process improvements.

• Lead and drive data science projects independently, owning the end-to-end process from data collection to model deployment. Apply advanced statistical and predictive modelling techniques to build, maintain, and improve multiple decision systems.
• Lead, mentor and guide junior data scientists in the team to deliver projects and outcomes for the business.
• Ability to write well designed, modular and optimized code.
• Work with technical experts to lead their teams and work towards the best solutions for the development of AI.
• Collaborate with stakeholders to identify opportunities to drive value with AI solutions. Partner with business and cross-functional teams to drive the development and integration of best-in-class AI solutions.

Essential Skills:

• More than 12 years of relevant experience in Data Science.
• Strong hands-on programming experience in Python (mandatory), R, SQL, Hive and Spark. Knowledge of H2O.ai, GitHub, Big Data and ML Engineering.
• Knowledge of commonly used data structures and algorithms.
• Solid foundation of Statistics and core ML algorithms at a mathematical (under the hood) level.
• Knowledge of Time Series, NLP and Deep Learning and Generative AI is preferred.
• Must have been part of projects building and deploying predictive models in production (financial services domain preferred) involving large and complex data sets.
• Understanding of principles of software engineering (source control, Agile/ scrum/ sprint).
• Excellent communication and interpersonal skills, with ability to effectively collaborate with cross-functional teams and influence decision making at all levels of organization.

Preferred Skills:

• Knowledge of Snowflake, AWS, Azure etc.
• Knowledge and hands-on experience in developing solutions with Large Language Models.
• Experience in Data Science in Sales and Marketing, Campaign Analytics, Ecommerce Retail or banking products for retail or business banking is preferred.
• Built and deployed large scale software applications.
• Proven track record of successfully leading data science initiatives from inception to execution, delivering tangible business results.
• Strong business acumen and ability to translate complex technical solutions into actionable insights for non-technical stakeholders.

Education Qualification: Bachelor's degree or Master's degree in Engineering in Computer Science/Information Technology.