The R&D Senior Manager – Data Science is a strategic leadership role responsible for advancing enterprise business intelligence and analytics capabilities across global R&D. This position combines deep technical expertise with portfolio-level strategy to accelerate innovation, improve decision-making, and strengthen cost competitiveness.

As a key enabler of digital transformation, this leader oversees a multidisciplinary team spanning data science, business intelligence, and systems management—translating complex materials and R&D data into actionable insights that drive business outcomes.

Strategic Leadership & Transformation

• Define and execute the enterprise R&D analytics and digital strategy to drive growth, margin expansion, and operational excellence

• Lead end-to-end portfolio governance, including investment prioritization, resource allocation, and roadmap alignment

• Champion the digital transformation of R&D, scaling advanced analytics, AI, and automation solutions

• Act as a thought leader on emerging technologies, identifying scalable opportunities to enhance innovation and competitiveness

• Establish governance frameworks to ensure data integrity, compliance, and execution discipline

Data Science & Advanced Analytics

• Set the direction for advanced modeling, optimization, and machine learning to solve complex R&D and business challenges

• Lead development of scalable analytics tools from concept through production deployment

• Drive adoption of analytics solutions to enable:

  • Portfolio optimization

  • Risk identification

  • Data-driven decision-making

• Oversee the creation and governance of data pipelines, data structures, and features required for advanced analytics

• Serve as a senior technical advisor translating complex data into business value

Systems & Digital Enablement

• Own the vision and governance for R&D systems and analytics platforms

• Partner with IT to design and deploy integrated, scalable digital solutions

• Advance enterprise capabilities in:

  • Knowledge management

  • Experimentation and modeling

  • Specification and product lifecycle data

• Ensure systems are scalable, secure, and aligned with enterprise architecture

Operational Excellence & Performance Management

• Establish and track R&D performance metrics, dashboards, and reporting frameworks

• Drive transparency and accountability through data-driven performance management

• Identify and scale high-impact analytics use cases that deliver measurable business results

People Leadership & Organizational Capability

• Lead and develop a high-performing, global team across data science, BI, and systems

• Build a culture of innovation, accountability, and continuous improvement

• Define and execute talent and capability strategies, including succession planning and skill development

• Mentor leaders and technical experts to strengthen organizational depth and impact

Cross-Functional & Executive Collaboration

• Act as a strategic partner to R&D, Operations, Procurement, Finance, Commercial, and IT leadership

• Align global and regional teams on standards, data governance, and best practices

• Translate business priorities into scalable analytics initiatives that deliver measurable value

• Ensure responsible and secure deployment of analytics solutions in partnership with IT and governance teams

• Scaled deployment of enterprise analytics solutions driving measurable ROI

• Increased speed and quality of R&D decision-making

• Strong adoption of AI and advanced analytics tools across the organization

• A high-performing, future-ready analytics organization

• Robust, trusted data infrastructure supporting innovation and growth

Required Qualifications

• MS or PhD in Data Science, Engineering, or a related field

• 10+ years of experience in data science, analytics, or R&D digital transformation

• 5+ years of leadership experience managing teams or complex cross-functional initiatives

• Proven track record of delivering business impact through analytics, systems, or operational leadership

Technical Expertise

• Advanced knowledge of:

  • Statistical modeling

  • Optimization techniques

  • Machine learning

• Proven programming skills in Python, SQL, and cloud-based data platforms

• Experience building data pipelines, models, and production-ready analytics tools

Domain Expertise (Preferred)

• Background in materials science, polymers, manufacturing, or packaging

• Familiarity with film extrusion or food packaging interactions

• Strategic thinker with strong business and operational acumen

• Proven ability to translate complex technical concepts into business value

• Influential leader with strong stakeholder management skills

• Highly collaborative, with the ability to drive alignment across global teams

• Results-oriented, with a track record of taking initiatives from concept to scaled impact

• Curious, innovative, and continuously seeking new ways to create value through data

• Ability to travel up to 25%