Data Strategy and AI/ML Product Management Lead

5 days ago

Islamabad, Islamabad, Pakistan Pakistan Single Window (PSW) Full time
Pakistan Single Window (PSW)

The role of Data Strategy and AI/ML Product Management Lead 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 defining a clear and concise product vision for AI/ML use cases within the new WeBOC system.

Phase 1: Data Strategy and AI/ML Product Vision

Data Strategy:

  • Collaborate with experts to understand the current WeBOC system's data landscape, stakeholder needs, and industry best practices.
  • 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.
  • Articulate the value proposition and potential benefits of AI/ML products within the WeBOC ecosystem.

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.
Phase 2: AI/ML Product Roadmap Development and Implementation Planning

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.
Phase 3: Implementation, Monitoring, and Continuous Improvement

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.
Requirements
  • 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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