Gilad (Ph.d) Gotesman-Applied Research | Decision Support | Investigation & Methodology

Designed and built an end-to-end interactive decision-support application using public European data across 27 EU countries and multiple strategic dimensions. Developed a structured analytical methodology for comparing countries, identifying patterns and trade-offs, and exploring strategic choices rather than presenting static dashboards. Translated complex multidimensional data into guided interactive exploration and learning workflows for non-specialist users. Built the application end-to-end using Python and Streamlit, with AI-assisted development and Git-based version control. Developed the project independently from problem framing and data analysis through methodology, UX logic, implementation and deployment.

Tools: Python, Streamlit, Git, AI-assisted development

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• Partnered with the CEO and management as a technical generalist across technology, operations, production scale-up, and customer problem-solving; owned the tech roadmap and KPI framework (e.g., future technology, machine performance, color fastness, color accuracy).
• Led cross-functional gap analysis across R&D, operations, and manufacturing to surface business risk and guide leadership decisions.
• Led the root-cause investigation, fine-tuning algorithm, and color-mixing innovation behind two of the company's key product and market breakthroughs (see Key Achievements).
• Built and scaled production-line assembly, QA, installation, and customer-support workflows supporting company-wide growth.

• Designed structured, reproducible testing methodologies (Design of Experiments) for evidence-based decision-making.
• Built a mass-balance model to support operational and business decisions (ink formulation and machine hardware) – later adopted as a long-standing reference tool for system and hardware selection.
• Investigated and optimized complex operational processes and system interactions.