Associate Director DDIT US&I Analytics Products Solutions Delivery

Job Description 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

Job Description

Roles and Responsibilities:

• 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

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.

Education:

• University Degree and/or relevant experience and professional qualifications

Skills and Knowledge

• Solid understanding of analytical and technical frameworks for descriptive and prescriptive analytics
• Good familiarity with AWS, Databricks, and Snowflake service offerings. Abreast of emerging technology within AI/ML space
• Strong collaborative interactions with customer-facing business teams.
• Track record delivering global solutions at scale.
• Ability to work and lead (a cross-functional team) in a matrix environment.
• 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 with sound foundation in Analytical Data life cycle management.
• Soft Skills - Consulting, Influencing & persuading, Unbossed Leadership, IT Governance, Building High Performing Teams, Vendor Management, Innovative & Analytical Technologies

Experience

• University Degree and/or 10 years relevant experience and professional qualifications

Commitment to Diversity & Inclusion:

We are committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.

Accessibility and accommodation

Novartis is committed to working with and providing reasonable accommodation to individuals with disabilities.

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Skills Desired

Budget Management, Business Acumen, Generative AI, Performance Management, Planning, Risk Management, Service Delivery Management, Stakeholder Management, Waterfall Model