• Improve: Be able to create custom solutions in HubSpot within the first 6 months. • Build: Understand business and revenue operations objectives and translate them into technical requirements. • Lead: Ability to map and integrate Multi-System Data Models • Drive: Ability to BLUF and communicate clearly to internal and external stakeholders • Plan: Ability to scope, plan, and deliver technically complex projects; documents architecture and workflows; communicate updates regularly

• Help define Circana’s overall approach and focus on the work with its strategic clients in the CPG vertical • Lead client third-party media measurement and audience activation for major CPG companies • Create strategies and programs to help large CPG advertisers increase their return on ad spend, sales lift, and other KPIs • Partner across key functions within Agency buyer and planner communities and ad network partners • Ensure our clients receive the highest level of sales and operational customer service • Leverage existing and innovative approaches to address evolving digital media challenges • Build and maintain strong working knowledge of current trends in the Marketing, Customer Relationship Marketing, Online Marketing, Market Research and CPG Industry • Present to internal and external c-suite and senior leadership results of business drivers • Facilitate product development through links to Circana’s commercialization partners • Serve as a thought leader in the media analytics space

• Lead and manage cross-functional project teams across the full lifecycle of data solutions implementations, from discovery through go-live and transition to managed services. • Serve as the primary point of contact for commercial data providers and pharma manufacturer stakeholders, ensuring alignment of data needs and compliance requirements, including HIPAA and BAA considerations. • Analyze business and data requirements and translate them into detailed project plans, functional documentation, and actionable implementation steps. • At times, document business and technical requirements including documentation of workflows, maps, models, data specifications, visualization requirements, etc. • Oversee delivery of solutions for: Channel and patient data aggregation (standard and custom feeds) Commercial Data Warehouse (CDW) and Master Data Management (MDM) implementations Data quality validation, harmonization, and transformation workflows Analytics platforms, dashboards, and reporting tools • Partner with internal data engineering, product, and client delivery teams to define and prioritize solution requirements and enhancements. • Provide project oversight across managed services, ensuring quality, consistency, and continuous improvement in recurring data operations. • Lead stakeholder meetings and status updates, facilitate issue resolution, and escalate risks as needed to maintain project momentum and customer satisfaction. • Support pre-sales and client scoping efforts by defining implementation approaches, timelines, and resource needs for proposed data solutions. • Leverage deep industry experience and understanding of pharmaceutical data standards to guide solution design and client recommendations.

• Design, develop, and deploy production-ready AI agents and multi-agent systems that automate enterprise business workflows. • Build reusable agent frameworks, orchestration patterns, and integration components that accelerate future client implementations. • Own the full software development lifecycle from proof of concept through production deployment. • Implement evaluation frameworks, guardrails, observability, and error handling for production AI systems. • Stay current with emerging AI models, orchestration frameworks, and agent technologies, incorporating new capabilities where they provide measurable business value. • Integrate AI agents with enterprise platforms through REST APIs, webhooks, OAuth2, and workflow automation technologies. • Design scalable approval workflows, routing logic, notifications, and intelligent automation supporting enterprise marketing operations. • Assess existing client workflows and identify opportunities to improve efficiency through intelligent automation. • Develop reusable integration patterns that simplify future client implementations. • Partner directly with client stakeholders to understand business processes and operational challenges. • Identify and prioritize high-value automation opportunities that reduce manual effort and improve business outcomes. • Rapidly prototype AI solutions, gather client feedback, and iterate toward production-ready implementations. • Present technical recommendations and solution approaches to both technical and business audiences. • Collaborate with architects, engineers, delivery managers, and consultants to deliver enterprise AI solutions. • Participate in solution architecture discussions, technical discovery sessions, and implementation planning. • Perform peer code reviews and promote engineering best practices across project teams. • Mentor fellow engineers on emerging AI technologies and integration patterns. • Support sales and solution teams by providing technical expertise during client pursuits, demonstrations, and solution estimation.