Gizem A.

Recently appointed to drive the roadmap and adoption of an AI-powered digital manufacturing products built on NVIDIA Omniverse and cloud-native architecture. Leading cross-functional collaboration across engineering, data science, and business stakeholders to integrate systems, optimize operations, and enable predictive, automated decision-making across the supply chain. Focused on building high-impact digital capabilities, driving platform adoption, and delivering measurable value through simulation, real-time insights, and digital twin technology.

Lead the development and implementation of a data and analytics strategy for the department, including the design and deployment of a data lake (Snowflake and Snaplogic). Collaborated with internal and external consultants, and managed complex stakeholder requirements to deliver a strategy that meets the needs of multiple business units. Lead a team of data engineers and BI developers, delivered advanced analytics and reporting solutions to the enterprise S&OP teams (~2000 users). Designed a new process for process defect management and closed the year with a 53% improvement in defect resolutions. People and operations management, lean, continuous process improvement, DevOps. - Legacy BI platform modernization, transformation of a critical forecasting digital product - Business Intelligence: Closely worked with stakeholders and user base for needs assessment, cost, development, execution, as well as user-testing and training. 50% performance improvement, and $300K savings each year.

Took ownership of a multi-year Worktools S&OP transformation initiative during a critical phase. Orchestrated alignment across business functions, built momentum, and drove progress on key milestones. Led cross-functional collaboration, established governance and accountability, and delivered early wins that built confidence and engagement.

Focusing on technology and strategy to improve and design the future of Sales and Operations planning. Projects include data strategy development, smart supply chain and advanced analytics applications. - Reduced Work Tools forecasting process time by 99%, lead the design and development of the new process. - Designed and developed a data process to increase forecast accuracy. - Lead development of dashboards which enabled visibility to facility and production data to decision makers.

Lead a variety of projects, mainly in supply chain portfolio. Role included preparing SOW, providing technical and non-technical coaching and development of the team members, as well as communicating with the customer in an agile fashion. Dealer Order Planning Solution – Supply & Operations Planning Leading a team of 5, we developed a solution where both the internal Caterpillar product and industry teams as well as external teams, our dealers, collaborate for placing machine orders. The solution is composed of a heuristic-based analytical python engine and a .net front. This project serves as the global machine order planning system, it is used by most of the machine business impacting billion dollar decisions each month. Solution provides alignment and a common methodology as well as supporting major differences between product groups. Undercarriage Component Wear Analytics – Product Support and Logistics Caterpillar collects part wear data from inspected machines, this project provides descriptive statistics, Tableau dashboards, and next generation of the project includes developing predictive analytics solutions to improve part sales. [System and method for estimating part wear based on environment Patent number: 10109121]

I developed solutions to improve processes, working with global teams, developed end-to-end solutions. Supply Chain Portfolio I designed and developed tools for existing and new processes to enable Caterpillar Production Systems business group decisions on • When and where to build products • Alternative sourcing decisions • Factory to dealer machine allocation; given constraints (i.e. production, demand, historical and market parameters) – a $1Billion question that was answered each month. (SAS, Python, Optimization modeling with Gurobi) Advanced Manufacturing Portfolio I developed several key supply chain related prescriptive and predictive analytics tools and processes, and applied them to create significant scenarios for the business partners ($1M R&D investment) • Leading the analytical modeling for Manufacturing Line Optimization • Supporting development of an optimization framework for complex manufacturing facilities as the optimization expert for strategic and operational level decisions (Routing, Scheduling, Slotting Optimization Tools) • Communications with projects partners (Python, Optimization modeling with Gurobi, and Tableau) Marketing Portfolio - Parts Pricing I supported the Customer Service Solutions business unit in Global Parts Pricing Strategy project ($6 billion revenue globally). My role included communicating and organizing work between four global teams for ETL mapping, data analysis, and validation efforts to understand and implement business strategies as well as provide support to parts pricing team to identify opportunities. (SAS) Internal and External Partnership Development • Analytics Now - developed content, scheduled and planned as well as general execution of the day-long conference. • People Team: Organized and created events for the analytics team. • Lead the 15th year celebrations. Managed all aspects of the celebrations - including the schedule, people, presentations and the reception. • Mentored and coached interns.

Artificial Intelligence Business Consortium (AiBC) Steering Committee helps faculty and students connect with industry, education, research, and the implementation of artificial intelligence solutions. AI in Supply Chain plays an important role, which will only grow over time. I am happy to contribute to the research agenda and participate in thought leadership along with the highly-qualified members from various industries. My participation in this committee is independent of my role at Caterpillar, Inc. For more please visit: https://www.luc.edu/leadershiphub/centers/aibusinessconsortium/about/steeringcommittee/

Teaching Machine Learning, Supply Chain Optimization, Python for Analytics,and Data Mining Principles, and Capstone courses at the Master of Science in Applied Data Science at the University of Chicago, Physical Sciences Division. Also serving as a capstone adviser and mentor.

Focused on the vulnerability of freight transportation systems, vulnerability, reliability, and resilience definitions and discussions in the context of multimodal transportation systems.

* Generated new research problems, worked on an inventory problem.

* Freight transportation data analysis, modeling, programming, and scenario applications. Projects: A Decision Support System for Transportation Infrastructure and Supply Chain System Planning (The University of Oklahoma, 05.2009 to 08.2011) Design and modeling scenario applications for the Decision Support System. Freight Flow Model for State of Oklahoma (The University of Oklahoma, August 2007 to May 2009) Modeling and programming freight flow applications for state of Oklahoma using TransCAD * Predicted freight congestion locations on roadways, railways, and waterways, used TransCAD, ArcGIS, VBA and Excel * Contributed to the development of a freight flow model for the state of Oklahoma * Developed freight transportation scenarios to analyze the role and the future of freight transportation in Oklahoma and US * Analyzed the economic influence of freight transportation in US, particularly in Oklahoma * Designed user interfaces for scenarios to be programmed

* Analyzed business procedures and designed business systems using Intellect

* Conducted analysis of the information system used and SharePoint application suitability

* Successfully contributed to production planning and inventory management

Dissertation focused on analysis of extreme event impact on freight movement and freight analysis and vulnerability. Other projects: * Analyzed freight flow movement in US (railways, roadways, and waterways), the economic influence on US, and developed scenarios that model freight behavior prior and after extreme events. * Participated in the Transatlantic Leadership Program organized by German-American Chamber of Commerce as one of the ten US delegates. Traveled to experience and learn about Germany’s state of the art and practice transportation and logistics facilities (May 2011). * Recommended process improvements in Medicare claim mailing process of Chickasaw Nation Industries, Inc. Estimated savings of $65,000 per year with a total cycle time reduction of 325%.

Thesis on U.S. Freight Flow Analysis Under an Extreme Condition: I-40 Bridge Collapse. Analyzed the impact of the bridge collapse on freight flow in Oklahoma, and US. * Recommended business expansion strategies to for a local business, with a discrete event simulation study developed in Arena.

Undergraduate, Exchange Student, Department of Computer Engineering * Spent two semesters at the Vienna Technical University as an Erasmus (exchange) student. Worked on a data mining project, using data mining software WEKA to extract underlying characteristics of a population data.

* Received full tuition scholarship * Focused on programming, learned C++, database design and management. Taken courses on Artificial Intelligence and Expert Systems.

* Received full tuition scholarship * Course work focus on statistics and simulation * Undergraduate Thesis: An Application of DOE using the Taguchi Approach. Successfully improved operations and quality at a plastic bag production facility (Goker Plastics) by minimizing noise factors in production.