Chapter Lead CDAO Decision Science Tech

As a Chapter Lead CDAO Decision Science Tech at CommBank, you will have a significant impact on the design, development, and deployment of state-of-the-art AI models within the Retail Banking sector. Your role involves leading and mentoring a team of talented data scientists to deliver high-quality solutions using machine learning, statistical modeling, and generative AI. Collaboration with stakeholders, product owners, engineers, and other teams is essential to develop and implement best-in-class AI solutions supporting group strategy. **Key Responsibilities:** - Develop and manage key modeling assets within the team, fostering a vision that utilizes state-of-the-art data science and statistical techniques. - Drive data science projects independently, from data collection to model deployment, applying advanced statistical and predictive modeling techniques. - Mentor and guide junior data scientists to deliver projects and outcomes for the business. - Write well-designed, modular, and optimized code. - Collaborate with technical experts to lead teams towards the development of AI solutions. - Identify opportunities to drive value with AI solutions, partner with cross-functional teams, and present complex results to senior stakeholders. - Define capability uplift roadmaps to enhance data science and decision science excellence. - Support the adoption of data science across the organization and contribute to strategic planning and direction of data science initiatives. - Stay updated on emerging technologies, enhance expertise in data science methodologies, and remain customer-focused to understand and address customer needs effectively. - Demonstrate strong problem-solving skills, critical thinking, fast learning capability, and effective communication. - Translate theories into practical applications to solve real-world problems. **Qualifications Required:** - 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. - Understanding of commonly used data structures and algorithms, as well as Statistics and core ML algorithms at a mathematical level. - Experience with Time Series, NLP, Deep Learning, and Generative AI preferred. - Previous involvement in projects building and deploying predictive models in production, preferably in the financial services domain. - Familiarity with software engineering principles, Agile methodologies, and source control. - Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams. - Education Qualification: Bachelors or Masters degree in Engineering in Computer Science/Information Technology. If you're seeking an opportunity to lead data science initiatives, drive innovation, and make a significant impact within a leading Australian bank, this role at CommBank could be the next step in your career.,