Role Purpose:

• Develop an Analytical Workbench capability to create advanced analytics product/services roadmaps from concept to development to launch, encompassing technology adoption, product engineering, service design, security and compliance, and business process change.
• Incubate and adopt emerging (GenAI, AI, NLP) technologies and launch products/services faster with rapid prototyping & iterative methods to prove and establish value. For identified technologies, launch to enterprise scale, ensuring value is derived.
• Focus and align DnA innovation efforts with the Business strategy, IT strategy, and legal/regulatory requirements.
• Establish and update strategies, implementation plans, and value cases to implement emerging technologies.
• Drive innovation (GenAI, AI/MLOPs, NLP) using appropriate people, processes, partners, and tools.
• Identify and develop advanced analytics capabilities & ecosystem partnerships in alignment with DnA strategy and in support of Enterprise Architecture and Integration.

Responsibilities

• Has end-to-end accountability for AWB services and products that are incubated, established, and delivered across cross-functional business areas.
• Serves as point of escalation, review, and approval for key issues and decisions.
• Take decisions on the AWB resource and capacity plans in line with Business priorities and strategies and close collaboration with delivery teams.
• Decide on continuous improvement within the team.
• Decides on the program timeline, governance, and deployment strategy

Key Performance Metrics:

Technology Adoption and Innovation:

• Number of emerging technologies (GenAI, AI, NLP) successfully incubated and adopted.
• Time to market for new products/services using rapid prototyping and iterative methods.
• Percentage of projects that move from prototype to enterprise scale.

Product and Service Development:

• Number of advanced analytics products/services developed and launched.
• Adherence to product/service roadmaps and timelines.
• Quality and security compliance of developed products/services.

Alignment with Business and IT Strategy:

• Degree of alignment between DnA innovation efforts and business/IT strategies.
• Compliance with legal and regulatory requirements in all initiatives.

Strategy and Implementation:

• Frequency and effectiveness of strategy updates and implementation plans.
• Success rate of value cases for implementing emerging technologies.

End-to-End Accountability:

• Customer satisfaction scores for AWB services and products.
• Number of cross-functional business areas successfully supported.

Resource and Capacity Management:

• Efficiency in resource and capacity planning.
• Utilization rate of allocated resources.

Continuous Improvement:

• Number of continuous improvement initiatives implemented.
• Impact of improvements on team performance and product quality.

Governance and Decision-Making:

• Effectiveness of governance frameworks and deployment strategies.
• Timeliness and quality of decisions made on key issues and escalations.

Collaboration and Team Performance:

• Feedback from cross-functional teams on collaboration effectiveness.
• Performance metrics for building and managing high-performing teams.

Vendor and Partner Management:

• Number of successful partnerships and collaborations with ecosystem partners.
• Vendor performance and compliance with agreed standards.

Skills:

• Emerging Technology Monitoring, Consulting, Influencing & persuading, Unbossed Leadership, IT Governance, Building High Performing Teams, Vendor Management, Innovative & Analytical Technologies.
• Strong understanding of descriptive vs. prescriptive analytical frameworks.
• Strong knowledge of MLOps and project life cycle management.
• Production experience with commercial and open-source ML platforms.
• Strong awareness of AWS ML service offerings.
• A product-centric approach to defining solutions. Collaborate with business in gathering requirements, grooming product backlogs, driving delivery, and ongoing data product enhancements.
• Agile delivery experience managing multiple concurrent delivery cycles.
• Emerging Technology Monitoring, Consulting, Influencing & persuading, Unbossed Leadership, IT Governance, Building High Performing Teams, Vendor Management, Innovative & Analytical Technologies.
• Solid understanding of Analytical and technical frameworks for descriptive and prescriptive analytics.
• Strong familiarity with AWS, Databricks, and Snowflake service offerings.
• Strong collaborative interactions with customer-facing business teams.
• Agile delivery experience managing multiple concurrent delivery cycles.
• Sound foundation in CRISP Analytical life cycle management

Education:

• University Degree and/or relevant experience and professional qualifications