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Trade Facilitation Data Strategist with AI/ML Expertise
5 days ago
The role of Trade Facilitation Data Strategist with AI/ML Expertise is a critical position at Pakistan Single Window (PSW). The successful candidate will be responsible for developing a comprehensive data strategy that outlines the principles, guidelines, and processes for managing, utilizing, and monetizing data within the PSW ecosystem. This includes identifying and prioritizing key AI/ML opportunities that align with PSW's strategic goals, national trade objectives, and stakeholder needs.
Key Responsibilities
Data Strategy and AI/ML Product Vision:
- Develop a clear and comprehensive data strategy document outlining the principles, guidelines, and processes for managing, utilizing, and monetizing data within the PSW ecosystem.
- Identify and prioritize key AI/ML opportunities that align with PSW's strategic goals, national trade objectives, and stakeholder needs.
- Articulate the value proposition and potential benefits of AI/ML products within the WeBOC ecosystem.
Phase 1: Data Strategy and AI/ML Product Vision
Data Strategy:
- Conduct market research and competitive analysis to identify opportunities and challenges for leveraging data as a product (DaaP) in the new WeBOC system.
- Develop a clear and comprehensive data strategy document outlining the principles, guidelines, and processes for managing, utilizing, and monetizing data within the new WeBOC ecosystem.
Ai/ML Product Vision:
- Based on the defined data strategy, develop a clear and concise product vision for AI/ML use cases within the new WeBOC system.
- Identify and prioritize key AI/ML opportunities that align with PSW's strategic goals, national trade objectives, and stakeholder needs.
Deliverables:
- A well-defined data strategy document.
- An AI/ML product vision document outlining the direction and goals for leveraging data and AI/ML in the new WeBOC system.
Ai/ML Product Roadmap:
- Develop a detailed product roadmap outlining the key AI/ML features, functionalities, and timelines for the WeBOC Transformation Project.
- Prioritize AI/ML products and features based on stakeholder needs, business objectives, technical feasibility, and potential impact.
- Collaborate with the Data & AI Architecture Lead to ensure alignment between the AI/ML product roadmap and the data architecture.
Implementation Planning:
- Develop a detailed implementation workplan for the new WeBOC system, outlining the key activities, timelines, dependencies, and critical path.
- Define a governance framework for risk management, conflict resolution, stakeholder engagement, and communication throughout the implementation process.
Estimate CapEx and OpEx:
- Collaborate with relevant technical leads to estimate the capital expenditure (CapEx) and operational expenditure (OpEx) pertaining to the data architecture required to cover data strategy as well as AI/ML use cases in the new WeBOC system.
- Gather inputs on hardware requirements, proprietary software tools licensing costs, and other relevant expenses.
- Develop a detailed budget and cost analysis for the project.
Deliverables:
- A detailed AI/ML product roadmap and regular progress reports on the AI/ML product development lifecycle.
- A comprehensive implementation workplan with a governance framework for risk, conflict management, stakeholder engagement, and communication.
- A detailed budget required to implement necessary data architecture in the new WeBOC system, including CapEx and OpEx estimates.
Support AI/ML Product Launch:
- Support the launch and rollout of AI/ML products within the new WeBOC system.
- Develop user manuals, training materials, and other resources to facilitate user adoption of AI/ML features.
- Collaborate with relevant experts and technical teams on this project to ensure smooth integration of AI/ML products into existing workflows.
Monitor and Evaluate AI/ML Product Performance:
- Establish metrics and tracking mechanisms to monitor the performance and impact of AI/ML products within the WeBOC ecosystem.
- Analyze user feedback and identify areas for improvement and refinement of AI/ML products.
- Collaborate with the technical team to implement necessary changes and enhancements.
Drive Continuous Improvement:
- Foster a culture of continuous improvement for data and AI/ML products within the WeBOC system.
- Stay abreast of emerging trends and best practices in data strategy, AI/ML product management, and trade facilitation to ensure the WeBOC system remains at the forefront of innovation.
Deliverable:
- Successful implementation and adoption of AI/ML products within the new WeBOC system, along with a framework for continuous monitoring and improvement.
- Bachelor's or Master's degree in Business Administration, Product Management, or a related field.
- 15+ years of experience in product management, product strategy, project management, or a related field.
- Experience of developing product strategies and project management of data management, governance, and AI projects.
- Experience of public sector data management, governance, and AI projects.
- Strong understanding of the product development lifecycle and agile methodologies.
- Experience in conducting user research and usability testing.
- Excellent communication, interpersonal, and stakeholder management skills.
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