Summary

As an Associate Director for Analytics Products Solutions Delivery, lead the development of an Analytical Workbench to create advanced analytics product roadmaps from concept to launch. This role involves creating advanced analytics product roadmaps from concept to launch, driving the adoption of emerging technologies such as GenAI, AI, and NLP, and ensuring rapid prototyping and enterprise-scale implementation. The ideal candidate will align innovation efforts with business and IT strategies, focusing on compliance and value creation. Responsibilities include overseeing end-to-end delivery of analytics services, managing resource planning, and fostering continuous improvement within the team. Expertise in MLOps, AWS, Databricks, and Snowflake, along with a strong foundation in agile delivery and CRISP analytical life cycle management, is essential

• 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.

• 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

• 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.

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

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

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

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

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

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

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

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

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

• 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

• University Degree and/or relevant experience and professional qualifications