Moritz Wüthrich

• • Led 15+ transformation programs, 5+ while managing teams of 2-5 consultants and $500K-$2M project budgets. Built reusable frameworks for pricing optimization, analytics strategy, and R&D process redesign

• • Directed delivery and execution of 15+ projects, prioritizing stakeholder requirements and synthesizing data-driven recommendations for decision-making of senior leadership

• • Led due diligence of a strategic joint venture partnership in the Middle East, resulting in the decision to invest over $1bn over 10 years, through effective stakeholder management

• • Built end-to-end analytics roadmap for CPG client's €2B global business units. Created prioritization framework evaluating 60+ use cases (demand forecasting, pricing optimization, customer segmentation), designed KPI tracking infrastructure, and developed change management plan for 1000+ commercial FTE. Delivered business case projecting 4-6% sales uplift (€80-120M annually), securing C-suite buy-in for 3-year implementation

• • Developed go-to-market strategies for digital product launches, through identifying and prioritizing target customer groups

• • Designed and implemented dynamic pricing system for €500M consumer electronics distributor, processing 50K+ SKUs across 8 European markets. Led cross-functional team building ML-based price optimization model (Python), created real-time pricing dashboards for 30+ category managers, and trained 50+ sales staff on new pricing playbooks. Delivered 2-3% margin improvement (€10-15M annual impact) within 18 months while maintaining revenue growth

• • Designed operational roadmap for pharma R&D transformation spanning 500+ scientists. Built prioritization framework evaluating 20+ AI use cases, created implementation timeline with resource allocation, for $75M+ cost reduction target. Navigated technical stakeholders (ML engineers, scientists), IT infrastructure teams, and C-suite to align on execution plan Reliability

• • Developed ML-based models for long-term forecasting of electricity prices, to support risk assessment for renewable energy assets, achieving 13-15% MAPE using GPR and ANN models

• • Led technical research and coding implementation in Python, coordinating relationship with Zurich based energy consultancy South Pole to refine market models

• • Built ML forecasting models (Python, TensorFlow, Gaussian Process Regression, Neural Networks) predicting 5-year electricity price trends for renewable energy risk assessment—achieving 13-15% MAPE. Demonstrated ability to translate complex technical work into stakeholder-ready insights. Managed technical relationship with energy consultancy (South Pole)

• • Reduced satellite panel repair time by 70%, by designing novel tool & repair process through operator interviews, tool CAD design, and rapid prototyping and testing. Rolled out process to team of 20+ operators

• • Developed MS excel model for operations and inventory planning at new production site, considering vendor deliveries and production capacities