Senior Data Scientist (cba)

Job Description

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 : Senior Data Scientist

Location : Bangalore

Business & Team :

The Chief Data and Analytics Office (CDAO) group delivers the groups data and AI solutions to ensure the highest levels of customer service through excellent insights, process excellence and AI innovation.

We deliver available, reliable, consistent technology solutions for our internal and external customers, essential tools for our people and innovative product platforms for our customers across the bank.

We put the customer at the center of everything we do and measure our performance against the groups’ external customer satisfaction measures.

Our team is composed of data scientists, engineers, and technology leaders, who bring in the right mix of skills to enable this transformation. We also work very closely with our business and operations colleagues to support these services which are critical to the Australian and Global economy.JOB IS FROM: italents.netVIEW

Impact & contribution :

The Senior Data Scientist will use technical knowledge and understanding of business domain to define, own, drive and deliver highly complex data science projects independently. You will be involved in and drive multiple initiatives in parallel.

You also will engage and collaborate with business stakeholders to clearly articulate findings to solve business problems.

Roles and Responsibilities:

• Lead and drive AI/ data science projects independently, owning the end-to-end process from data collection to model deployment.
• Apply Gen AI, NLP, Computer Vison, Deep Learning, advanced statistical and ML predictive modelling techniques to develop and implement scalable AI solutions, ensuring accuracy and reliability of models.
• Collaborate with business and cross-functional teams to understand their needs and implement AI driven solutions.
• Opportunity understanding/ problem formulation and suggest AI solutions to help the business for maximum impact.  
• Mentor junior data scientists and provide guidance on their projects.
• Present complex results to non-technical stakeholders, translating data insights into actionable business strategies.
• Develop and deploy production-grade AI/ machine learning models in cloud-based and on-prem platforms.
• Lead cross-functional teams in the design and execution of AI/ data science projects, ensuring alignment with business objectives.
• Stay abreast of emerging technologies and industry trends, continuously enhancing expertise in AI/ data science methodologies and tools.
• Drive complex business problems through data analysis and AI/ ML modelling.
• Strongly support the adoption of AI/ data science across the organization.
• Contribute to the strategic planning and direction of AI/ data science initiatives within the organisation.
• Engineering: working in a multidisciplinary squad alongside architect and data engineer

Essential Skills:

• More than 10 years of relevant experience
• Strong hands-on programming experience in Python (mandatory), R, SQL, Hive and Spark.
• Ability to write well designed, modular and optimized code.
• Knowledge of GitHub, Big Data and ML Engineering.
• Knowledge of Snowflake, AWS, Azure etc.
• Knowledge of AI, Deep Learning, Natural Language Processing (NLP), Computer Vision, Large Language Models (LLM), Generative AI (e.g., Open-source models & GTP’s, RAG, Guardrails for fairness / privacy).
• Knowledge and hands-on experience in developing solutions with Large Language Models.
• Must have been part of projects building and deploying AI/ predictive models in production (financial services domain preferred) involving large and complex data sets.
• Model Deployment Experience (MLOps)
• Demonstrated expertise through blogposts, research, participation in competitions, speaking opportunities, patents and paper publications.
• Most importantly - ability to identify and translate theories into real applications to solve practical problems.
• Solid foundation of Boosted Trees, Time Series, Statistics and core ML algorithms at a mathematical (under the hood) level.
• Experience in Data Science in Sales and Marketing, Campaign Analytics, Ecommerce Retail or banking products for retail or business banking is preferred.

Qualification: Bachelor’s degree in Engineering in Computer Science/Information Technology. Masters or Ph.D. preferred.