Job
Description
We are seeking a Solution Delivery Manager to lead our Global Supply Chain Data & Analytics team at Novo Nordisk. Apply Now and join us in driving innovation and excellence in our data-driven solutions! The position You as a Solution Delivery Manager towards Global Supply Chain Data & Analytics will lead the tactical direction, development, and execution of the company s data-driven initiatives with a focus on Global Supply Chain as well as interfacing functions within the Product Supply and Quality domain. Key responsibilities for the role are: Data strategy & leadership : Develop and implement a tactical road map in close collaboration with LoB (Line of Business) to deliver on Global Supply Chain s strategic aspirations within Data & Analytics. You shall act as a trusted partner within Data & Analytics towards Global Supply Chain, ensuring seamless integration of data from various sources (e.g., SAP, MES, Demand forecast, quality deviation) to Global Supply Chain pipelines. You shall ensure adherence to corporate data governance frameworks to ensure data quality, security, and compliance with regulatory standards (e.g., FDA, EMA, HIPAA). Advanced Analytics & Innovation : Lead the development and maintenance of data, advanced analytics products and platforms utilizing machine learning, AI (Artificial Intelligence), to drive business value in Global Supply Chain. Foster a culture of innovation, ensuring the team stays at the forefront of emerging technologies, such as AI-driven Digital twin, control towers. Technology Infrastructure & Tools : Oversee the design and management of scalable data architecture and technology platforms that support high-volume data processing (e.g., cloud-based infrastructures, data lakes). Oversee the management and integration of ERP, MES, SCM, QMS, sensor / IOT data, to support strategic aspirations in Global Supply Chain. Cross-Functional Collaboration : Partner with business teams to identify opportunities for leveraging data and analytics to drive improved technical operations. Partner with IT team supporting line of business to ensure the data and analytics solutions are well integrated in business architecture and business portfolio. Team Leadership & Development : Build and lead a high-performing and distributed team of product managers, data engineers, scientists, analysts, and technologists. Mentor and develop staff, fostering a data-driven culture and ensuring continuous professional growth within the team. Compliance & Risk Management : Ensure all data activities are compliant with global regulatory requirements and industry standards (e.g., GxP, 21 CFR Part 11). Oversee risk management strategies related to data privacy, security, and ethical use of data in Commercial. Maintain up-to-date knowledge of regulatory changes and drive compliance initiatives to minimize business risk. Performance Metrics : Manage and execute product portfolio within timeline, quality, budget. Ensure data and analytics are being used to drive informed decision-making across departments. Evaluate the development and retention of top talent, as well as team engagement and satisfaction. Qualifications To succeed in this role, you have: Master s degree or PhD in Data, Data Science, Computer Science, AI, or a related field. Overall 12+ years of experience as Data practitioner, with proven experience moving ideas into productive solution in a regulated industry and 5+ years of experience in data and analytics in Engineering leadership roles, with at least 3 years in life sciences or pharmaceutical industries in supply chain, manufacturing, and or quality is desirable. Proven track record of leveraging data and analytics to drive supply chain optimization, manufacturing efficiency in a highly regulated environment. Deep expertise in ERP, MES (Manufacturing Execution System), SCM (Supply Chain management), QMS (Quality Management System), Digital twins tools. Experience managing large-scale data platforms, including cloud computing, data lakes, and advanced analytics technologies. Familiarity with regulatory requirements and data standards specific to the life sciences. Experience working with cross-functional distributed teams. Experience with emerging technologies like IoT (Internet of Things), AI. Leadership and communication skills, with the ability to influence at various levels of the organization. Ability to work effectively in a matrix organisation. Adaptable to different situation and able to work with ambiguity. Ability to improve business process to demonstrate pragmatic use of data and AI and deliver impact.
