• Managing overall workload of agency digital analytics team, determine prioritization and staff assignment for each project; • Leading the agency’s digital analytics team in providing excellent analytical support to agency clients; • Collaborating with departments to understand their needs and navigating priorities; • Developing and improving processes to document and automate key performance indicators and communicate insights to clients and internal stakeholders, including the executive leadership team; • Working with other teams, including engineering and data science, to constantly improve data reliability and quality; • Conducting quality assurance checks on the analytics team’s work and connecting pieces to define broader goals.

• Adheres to Integer’s Values and all safety, environmental, security and quality requirements • Lead the establishment and execution of the global SIOP processes for all of Integer • Execute all facets of the SIOP process to provide an optimum customer service level and working capital performance • Partner with marketing and sales, to ensure the demand consensus process delivers an agreed upon, workable volume forecast • Integrate NPI, EOL, LTA’s, Support/Service requirements, Market data, and other product demand signals to create a demand forecast • Collaborate with Product Management, Marketing, Sales, Engineering, Support, Logistics, Supply Chain, Finance • Lead the SIOP management reviews, prepare all data and metrics for review • Create the SIOP minutes, communicate key conclusion to stakeholders and perform follow up of the actions • Recommend optimal inventory levels at various stages in the supply chain • Ensure smooth transition of demand from NPI from Engineering/Product Management to Mass Production • Analyze supply and demand issues and facilitate resolution throughout the supply chain • Assist in quantifying and defining scope for capacity, resource, logistics, and supply chain planning • Evaluate supplier delivery performance and capability • Maintain forecasts and manage links between systems for forecasting, master production scheduling, inventory management, and product development • Facilitate a global Executive SIOP process for Executive Leadership team • Document and share “best practice” methods, processes, and ideas across the business’s supply chain operations • Identify opportunities to reduce the cost of sales and operations planning

• Define and execute the enterprise analytics roadmap aligned with business objectives • Foster a culture of data-driven decision-making across departments • Manage and mentor a team of analysts, data scientists, and BI developers • Oversee design and implementation of analytics products and solutions using Databricks, modern Business and Artificial Intelligence tools and Agile principles • Champion data governance and build data stewardship and literacy across the business • Drive adoption of data products to scale data value • Implement predictive modeling, statistical analysis, AI and machine learning where applicable • Leverage Python for advanced analytics, automation, and integration with Databricks workflows • Stay current with emerging technologies and recommend enhancements to the analytics stack • Monitor and manage Analytics services demand, aligning expectations and delivery to highest priority and value • Partner with business leaders to identify analytics opportunities and deliver actionable insights • Present findings and recommendations to executive leadership in clear, compelling formats

• Develop long-term market and opportunity models that quantify potential, guide prioritization, and support product and portfolio decisions. • Leverage advanced analytics (e.g., predictive modeling, correlation and scenario analysis) to generate forward-looking insights that inform strategic roadmaps. • Translate insights into derivative analyses in support of business cases for key strategic bets. • Collaborate across Product, Finance, Commercial, and Market Access to align assumptions, inputs, and scenarios. • Synthesize internal and external data – market trends, adoption dynamics, customer behavior, and competitive shifts – into clear, actionable insights. • Present analytical findings, scenarios, and recommendations to senior leadership with clarity and strategic relevance. • Define and evolve frameworks for opportunity sizing, market segmentation, and scenario planning.