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Data Scientist Senior Manager

2 weeks ago


Park Road, Singapore Commonwealth Bank Full time

**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 Manager

**Location**:Bangalore

**Business & Team**:Business Banking - Data Science

**Impact & contribution**:As a Senior Manager in the Business Bank’s Customer, Channels & Data AI Centre of Excellence (CCD - AICE), you will play a key role in developing & executing AI initiatives and strategies. Using your powerful combination of leadership skills and hands-on knowledge, you’ll foster a growth orientated culture of sharing, learning and problem solving across teams by focussing on cutting-edge deep learning and generative AI techniques. Your role will have a significant impact on our innovation capabilities and business processes by leveraging these advanced technologies.

**Roles & Responsibilities**:

- Lead data-driven initiatives, from problem formulation to model deployment, from leveraging advanced statistical techniques, machine learning algorithms to GenAI Solutions
- Drive the development and implementation of scalable data solutions, ensuring accuracy and reliability of models.
- Collaborate with business stakeholders to define project goals, prioritize tasks, and deliver actionable insights.
- Design and execute experiments to evaluate model performance and optimize algorithms for maximum efficiency.
- Develop and deploy production-grade machine learning models in cloud-based and on-prem platforms.
- Multi-Agent System Design: Architect and deploy multi-agent systems, enabling AI agents to collaborate, share knowledge, and solve tasks dynamically, Develop frameworks for agents to interact effectively using generative AI for reasoning, task execution, and learning.
- Production Deployment: Manage and oversee the deployment of at least one Generative AI model or multi-agent system in production, ensuring operational excellence and high availability.
- Strategic Leadership: Collaborate with stakeholders to identify opportunities for Generative AI and multi-agent systems, define use cases, and create actionable strategies for implementation. Drive thought leadership in multi-agent architectures and Generative AI innovation.
- Mentorship: Mentor junior team members in building and deploying Generative AI models and multi-agent systems.
- Research and Development: Drive internal research initiatives and contribute to the AI community through papers, patents, or open-source projects in Generative AI and multi-agent systems.

**Essential Skills**:

- 12+ years of experience in Data Science and GenAI
- Outstanding delivery and running of large and complex data and AI programs
- Ability to lead and inspire people to deliver exceptional outcomes and to drive a strong performance culture
- Experience in agile methods at scale, experiment driven innovation, and a measurement culture.
- Is an an experienced AI leader who can inspire a team of data scientist as a technical leader, and innovation thinker and someone that can make things happen. This leader needs to be a self-driven individual who is willing to propose changes, as well as execute them.
- Is aware of the AI landscape, and it can ensure the bank stays in the cutting edge of the technology.
- Great structured thinker & creative problem solver who can design and deliver solutions that meet stakeholder needs while powering through many constraints and dependencies.
- Experience in building teams and good understanding of global team management as well as operating model.
- A deep industry and technical knowledge
- Ability to coordinate and engage with multiple stakeholders (both business and technology)
- Advanced knowledge of multi-agent design principles, agent-based simulations, and reinforcement learning for multi-agent systems.
- Expertise in transformers, GANs, VAEs, and Diffusion Models.
- Strong grasp of optimization techniques like quantization, pruning, and knowledge distillation

**Education Qualifications**:Bachelor’s degree in Engineering in Computer Science/Information Technology

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