Project Planning and Execution
- Develop comprehensive project plans that outline scope, objectives, deliverables, timelines, and resource requirements.
- Oversee the execution of projects related to data analytics and AI, ensuring they are delivered on time and within budget.
- Coordinate with data scientists, data engineers, business analysts, and other stakeholders to align project goals with business strategies and regulatory requirements.
Stakeholder Management and Communication
- Serve as the primary point of contact for all project-related communications.
- Facilitate regular meetings, provide progress updates, and manage expectations with internal stakeholders, such as senior management, risk and compliance teams, and external partners.
- Ensure that all stakeholders are informed and engaged throughout the project lifecycle, addressing concerns and adapting plans as necessary.
Risk Management and Compliance:
- Identify, assess, and manage project risks, including technical, operational, and compliance-related risks.
- Develop mitigation strategies to address potential issues and ensure project alignment with industry regulations, such as GDPR, AML, and KYC.
- Monitor and report on risk status, ensuring all data and AI initiatives adhere to the bank’s data governance and compliance policies.
Generative AI Integration and Implementation
- Design and oversee the integration of generative AI solutions into business processes to enhance efficiency and innovation.
- Collaborate with AI specialists to identify use cases for generative AI, such as natural language generation, predictive modeling, and automated content creation.
- Ensure the ethical and responsible use of generative AI by implementing guidelines for bias detection, transparency, and accountability.
- Train teams and stakeholders on the capabilities, limitations, and practical applications of generative AI to foster adoption and informed decision-making.