Strategic Data Governance Lead

2 weeks ago

Singapore beBeeDataGovernance Full time $120,000 - $180,000

The role of Strategic Data Governance Lead is crucial in driving the firm's data strategy with a strong focus on governance, risk management, and compliance.

Key responsibilities include bringing a strong risk and control mindset to identify, interpret, and apply governance frameworks and policies related to data, cloud, and AI. This involves playing a key role in assessing and managing emerging technology risks, including the responsible use of Generative AI and ethical considerations for AI development.

An essential part of this role is ensuring governance practices are embedded throughout the data and AI lifecycle, closing gaps in compliance and operational risk exposure. This includes supporting the automation and modernization of control frameworks using advanced analytics and AI/ML to enhance control effectiveness and efficiency.

Achieving this goal requires embedding governance and compliance checkpoints within automated pipelines to ensure robust monitoring, alerting, and auditability. The successful candidate will lead the development, testing, and deployment of AI/ML models aligned with model governance standards, ensuring performance, transparency, and regulatory compliance.

This individual will define and implement best practices for model validation, lifecycle management, and controlled upgrades. Additionally, they will work cross-functionally with data engineers, software developers, and risk professionals to integrate governance and risk requirements into data and AI initiatives.

The ideal candidate will have a Master's degree in Data Science, Computer Science, Information Systems, Economics, Operations Research, or a related field. They should have 10+ years of experience in data and analytics, with a strong emphasis on governance, risk, and compliance. Proven track record in building and optimizing AI/ML models, with deep understanding of model governance and regulatory alignment, is essential.

A background in cloud platforms (AWS, GCP, or Azure), especially with their governance and security features, is desirable. Proficiency in handling complex data types (structured, semi-structured, unstructured) within regulated environments is also required. Demonstrated ability to assess and apply responsible AI frameworks, manage AI risks, and implement effective controls is necessary.

The successful candidate will possess strong communication skills, with the ability to engage stakeholders on risk mitigation, governance obligations, and strategic data use. Solid knowledge of SDLC standards, including integration of data governance and application-level controls, is expected.

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