The Job
Strategic Planning and Roadmap Development:
- Develop a strategic roadmap for AI implementation aligned with business goals and objectives.
- Identify opportunities for AI adoption across various business functions and define priorities for implementation.
Technical Evaluation and Implementation
- Collaborate with cross-functional teams to design AI and data management solutions that meet business requirements and technical specifications.
- Evaluate and select AI and Data related technologies, tools, and platforms to support implementation efforts.
- Integrate AI and Data management solutions with existing systems, infrastructure, and processes, ensuring compatibility and seamless operation.
- Evaluate and select data management technologies, platforms, and tools to support data architecture initiatives, considering factors such as scalability, performance, and cost-effectiveness.
- Stay abreast of emerging technologies and industry trends in AI and data management, analytics, and cloud computing
Architecture Governance and Compliance:
- Establish architecture governance processes to ensure adherence to data architecture principles, standards, and guidelines.
- Monitor compliance with regulatory requirements, industry standards, and best practices related to data management and security.
Project Management and Execution:
- Lead the planning, execution, and monitoring of AI implementation projects, ensuring adherence to timelines and budgets.
- Coordinate with internal teams, external vendors, and stakeholders to drive project delivery and mitigate risks.
Change Management and Adoption:
- Develop change management strategies to facilitate the adoption of AI solutions by end-users and stakeholders.
- Provide training, documentation, and support to ensure successful deployment and utilization of AI technologies.
Resource Management and Team Leadership:
- Build and lead a team of AI engineers, data engineers, and/or other professionals responsible for implementing AI solutions.
- Provide guidance, mentorship, and support to team members, fostering a culture of innovation, collaboration, and excellence.
- Stakeholder Management:
- Serve as the primary point of contact for stakeholders, providing regular updates on project status, milestones, and outcomes.
- Collaborate with business leaders, users, and other stakeholders to understand requirements, gather feedback, and ensure alignment with project goals.
Risk Management and Compliance:
- Identify and assess risks associated with AI projects, including technical challenges, resource constraints, and regulatory compliance issues.
- Develop and implement strategies to mitigate risks and ensure compliance with relevant laws, regulations, and ethical standards.
- Performance Evaluation and Continuous Improvement:
- Evaluate the success of AI projects based on predefined metrics and KPIs, analyzing outcomes and identifying areas for improvement.
- Drive continuous improvement initiatives, incorporating lessons learned and best practices into future projects to optimize performance and outcomes.
Job Requirement
- Minimum Bachelor’s degree in computer science, engineering, data science, or related field. A Ph.D. is a plus.
- Proven experience (5 years or more) leading AI and/or Data management projects from conception to delivery, preferably in a corporate or enterprise environment.
- Deep understanding of data management principles, data modeling techniques, and database technologies.
- Experience with data integration, ETL processes, data governance, and metadata management.
- Proficiency in data architecture tools and platforms (e.g., ERwin, SAP PowerDesigner, Informatica)
- Strong technical expertise in AI technologies and Data management, including machine learning, deep learning, natural language processing, and computer vision.
- Technical understanding to perform and lead data management practices – Data quality improvements, Data engineering – Experience in Python/DB programming languages – SQL is a must.
- Excellent project management skills, with the ability to effectively plan, organize, and prioritize tasks in a dynamic environment.
- Strong leadership and communication skills, with the ability to inspire and motivate team members, build consensus, and influence stakeholders.
- Experience with agile or other iterative project management methodologies is desirable.
- Demonstrated ability to navigate complex organizational structures, manage competing priorities, and drive results in a collaborative, cross-functional environment.
- Certification in enterprise architecture (e.g., TOGAF) or data management (e.g., DAMA) is a plus
