Director, R&D - Digital Transformation

Job Description

Job Purpose

The Director, R&D - Digital Transformation is a senior leader responsible for defining the digital transformation strategy for the NA R&D organization and building the capabilities required to deliver it. This is a greenfield role , as the Director will establish the vision, design the operating model, and develop the target-state organizational structure and multi-year resourcing plan needed to scale a high-performing, multidisciplinary Digital R&D function.

The role will have three to four direct reports to support our digital transformation agenda , with organizational design and hiring owned directly by this leader.

In practice, the Director leads a centralized Digital NA R&D Hub , partnering with the NAZ Platforms, R&D and IT teams to deploy predictive models, AI-enabled tools, advanced data architectures, and digital twin capabilities that accelerate innovation, reduce physical iteration, and shorten time-to-market. This individual will drive the definition, development and adoption of the new digital workflows and ways of working for the R&D Organization.

This leader sits at the intersection of food and materials science, process and packing engineering, data science, and manufacturing and will closely collaborate across functions and disciplines to bring the transformation agenda to reality.

Essential Functions & Responsibilities

• Own the R&D digital transformation agenda. Translate organizational ambition into a phased, prioritized strategic roadmap , defining required capabilities, sequencing investments, and securing senior leadership alignment and resources. Connect the roadmap directly to enterprise value: top-line growth, productivity , sustainability commitments, and time-to-market competitiveness.

• Own organizational design for the NA Digital R&D team . Define the target-state team structure, capability architecture, and workforce plan required to operate ermine the optimal mix of internal talent, external hires, and strategic partners. Establish hiring profiles and development pathways for a multidisciplinary team spanning data science, ML engineering, and R&D domain expertise , including but not limited to Product Development, Consumer Science, Process and Package Development.

• Lead integration of legacy PLM, ELN, and LIMS systems into a cohesive data platform in partnership with R&D Transformation. Define governance protocols ensuring ingredient specifications, packaging tolerances, sensory data, and process parameters share a universal taxonomy. Establish the data quality standards and ingestion pipelines required to power reliable AI and predictive analytics at scale.

• Lead development and deployment of physics /engineering /chem
  -based simulation, machine learning, and generative AI models that predict consumer acceptance/behaviors, formulation performance, process behavior, shelf-life, and packaging integrity prior to physical trials. Define MLOps infrastructure and model governance practices to move from proof-of-concept to production-grade tools. Guide build-vs-buy decisions for digital R&D platforms in partnership with IT

• Design and operationalize a scalable Hub-and-Spoke engagement model enabling rapid, repeatable adoption of digital tools across Central and Platform R&D teams. Establish workflows, decision rights, and governance mechanisms to support effective collaboration across geographies and disciplines.

• Recruit, develop, and retain professionals who can translate between scientific problem statements and digital solutions. Champion digital fluency across the broader R&D organization through training, embedded Spoke partnerships, and storytelling that connects digital tools to commercial outcomes.

• Serve as the senior advocate for digital R&D transformation. Build cross-functional coalitions with R&D, Operations, IT, Marketing, and Quality. Drive adoption through proof-of-concept delivery, measurable value creation, and consistent executive engagement.

• Team (salaried ): 2 to 4 direct reports .

• Innovation Velocity & Market Impact

• Time-to-Market Reduction:
  Decrease in idea
  -to-commercialization cycle time for new product development and packaging transitions . Reduce number of line trials and associated cost .

• Agile Sprint Velocity:
  Digital innovation sprints completed per quarter resulting in a viable commercial brief

• Right
  - First-Time :
  Increase overall quality of delivery of projects, measured as % of right first time initiatives to market (no intervention needed after launch)

• Organizational Design & Capability Build

• Org Design Completion:
  Approved future-state organizational structure and resourcing roadmap delivered within 12 months

• Transformation Roadmap Adoption:
  Executive-aligned digital R&D strategy approved within 6 months

• Resource Efficiency & Predictive Accuracy

• Physical Iteration Reduction:
  Decrease in benchtop iterations or pilot plant /plant trial runs required per project , and…