• Lead hands-on development and delivery of analytics solutions by architecting and troubleshooting as needed, driving the creation of enterprise data models, data products, analytical datasets, and SAC reporting assets, while prioritizing SAP-delivered content and ensuring adherence to best practices and fit-to-standard principles. • Execute the enterprise analytics strategy by driving the roadmap aligned to business transformation goals, advancing SAP Business Data Cloud and AI-enabled capabilities, establishing architecture and governance standards, mentoring technical teams, and partnering with business stakeholders to deliver scalable analytics solutions. • Design end-to-end analytics solutions by creating scalable architectures across SAP Business Data Cloud, Datasphere, SAC, S/4HANA Embedded Analytics, BTP, and intelligent data products, while developing robust data models, establishing governed semantic layers, and enabling seamless integration between SAP and non-SAP data sources. • Collaborate with business stakeholders to gather requirements, translate them into technical designs, and deliver high-quality solutions. • Optimize performance, scalability, and security of analytics platforms. • Drive adoption of new SAP BDC features, staying ahead of industry trends and advising on best practices. • Drive enterprise-wide adoption of common KPIs, business definitions, and semantic models. • Ensure compliance with security, privacy, and regulatory requirements. • Provide technical leadership, mentoring, and guidance to developers and analysts. • Own IT service delivery for assigned manufacturing sites, maintaining strong relationships and ensuring operational excellence. • Collaborate cross-functionally to deliver IT services aligned with business needs during organizational transitions, including separation activities. • Participate in the design and implementation of secure, scalable, and reliable technology solutions that support core business operations and digital transformation. • Ensure manufacturing connectivity and data flow across enterprise systems, enabling efficient production and supply chain processes.

• Contribute to the design and build intelligence systems that help Liquid Engine understand workflow context, track change over time, and support consistent outputs • Translate creative and production workflows into structured representations such as entities, relationships, rules, and graphs • Help develop systems for tracking state, version history, provenance, and dependencies across workflows • Build rule-based and heuristic systems that identify conflicts, evaluate consistency, and surface issues before they create downstream problems • Support change impact analysis by helping the system reason about dependencies, cascades, and workflow consequences • Develop evaluation frameworks that measure system usefulness, output quality, and reduction of manual rework • Partner with engineering on event pipelines, data models, and system architecture that support intelligent system behavior • Contribute to explainable recommendation and decision-support systems grounded in workflow context • Help define telemetry, measurement, and governance approaches for intelligence features across the platform

• Own the end-to-end lifecycle of production machine learning models, from problem definition through deployment and ongoing optimisation. • Design, build and deploy artificial neural network and machine learning models for vehicle valuation, pricing and other analytics. • Take responsibility for production model performance, reliability and long-term maintenance. • Evaluate model performance and improve predictive accuracy across production models. • Develop and maintain automated retraining pipelines to keep models effective over time. • Monitor deployed models, investigate issues and implement improvements to ensure models remain accurate and reliable. • Design and run experiments, track results and use data to drive model improvements. • Work closely with engineering and product teams to integrate models into production systems and deliver business value.

• Provide data management support by assisting with data processing, including downloading, processing, cleaning, documenting, consolidating, archiving, and transferring of data in various files formats. • Provide data management support to by posting of data in various file formats and locations. • Document the development and implementation of data collection methods and protocols. • Manage and update Power BI dashboard. • Experience modernizing surveillance systems, including but not limited to converting SAS code to Python/R. • Automate reoccurring reports, tables, and presentations of data for the team to access on a routine basis. • Create and manage quality assurance programs for daily downloads from website. • Provide analytic support including regular and ad hoc epidemiologic and statistical analyses. • Produce reports, tables, and presentations of the data.