VP, AI Product Manager, Transformation Group
3 weeks ago
Business Function
Here at the DBS Transformation Group, we focus on nurturing the culture of the "World's Best Bank" (Euromoney 2018, 2019 and 2020). Our approach is a combination of both science and art. We immerse our stakeholders in the world of design thinking and experimentation, drive rigorous creativity along our innovation pipeline, and build connections between corporate entrepreneurs and start-ups. We are a cross-disciplinary team focused on the invention of solutions that will radically improve the way people live, work and play. We are passionate and committed to making banking joyful (while having lots of fun)
Job Purpose
AI Product Manager for a product that is a knowledge repository utilized by the business and data chapter for discovery, reusability, and AI governance of AIML use cases and models across the bank.
Responsibilities
- Product Management: defines and shapes product to effectively drive AI industrialization across the Data Chapter. Align with stakeholder requirements, prioritizes initiatives, and maximizes impact of the features.
- Product Development: leads the development of product with a team of developers (primarily located in India or consisting of junior staff), fostering collaboration and driving efficient execution to deliver impactful features on schedule.
- User-Centric Approach: champion data analytics user needs, ensuring product decisions are informed by user feedback and empirical data by building reports, data management and maintaining dashboards. This results in valuable solutions that improve user experience.
- Technical Integration: bridge technical gaps by integrating product with other ADA tooling (ML development & deployment tools) across the ML lifecycle, enabling improved data insights and reducing toil for ALAN users.
- AI Governance: implement features and functionality for AI Governance in product, ensuring a deep understanding and compliance with audit and MAS requirements.
- EVP Data Community: builds, supports, and maintains EVP data community initiatives, fostering quality networking and providing a knowledge-sharing platform for Data Chapter members
Requirements
- Technical Proficiency: 3-5 years experience
- Software Development: Proven background in software development with expertise in developing systems and products in financial services industry from reputable education program.
- Programming Languages: Proficient in R, Python, SQL, and web technologies.
- Data Lake Technologies & Architectures: Strong understanding of data lake technologies and architectures.
- Tooling & Platforms: Familiarity with tools such as CML, Jupyter Notebooks, duckdb, superset, tableau, and QlikView – commonly used in DBS. This helps with data management, reporting, and product management.
- ML Lifecycle, AI Industrialization, AI Governance & ADA: 3-5 years of experience
- DBS AI Industrialization: Strong understanding of the DBS AI industrialization journey, including technological and infrastructure limitations, required for product management & integration of ALAN across tools used by its business and technical users.
- AI/ML Life Cycle: Deep understanding of the AIML lifecycle, enabling effective communication across technical, functional, and business contexts with key product users who are Data analytics members.
- Data Analytics Expertise: Experience working with Data Scientists, Data Analysts, and Data Translators in a banking context.
- AI Governance & Compliance: In-depth understanding of complex risk environments (regulatory, operational, and financial) and the ability to ensure product features effectively captures AI Governance requirements and MAS regulations (e.g., feature, veritas, transparency, model monitoring, fairness).
- Product Management & Stakeholder Engagement: 3- 5 years of experience
- Product Management: Proven experience in product management, including community building, user engagement, and product adoption. Successful examples of managing an AI product for analytics users in regulatory and governance context.
- Stakeholder Management: Exceptional ability to build and manage relationships with both technical development teams and Data Chapter teams across all levels, from junior analysts gathering feedback to senior leadership presenting product strategies to ED/MD for product.
- Communication & Presentation: Demonstrate strong communication skills and experience & ability to present business value metrics and deliver concise advice, both orally and in writing, to senior leaders and board-level management
Apply now
We offer a competitive salary and benefits package and the professional advantages of a dynamic environment that supports your development and recognises your achievements.
Tell employers what skills you haveTableau
Invention
Experimentation
Industrialization
Data Management
User Experience
Transparency
Web Technologies
Stakeholder Engagement
Product Management
Networking
Design Thinking
Product Development
Bridge
Stakeholder Management
Data Analytics
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