• Serve as the primary point of contact for SCCAF-related coordination between clients, contractors, and Olsson's engineering teams. • Manage SCCAF project schedules and align study milestones with construction timelines. • Coordinate the development and delivery of SCCAF reports, settings, labels, RFIs, and submittals. • Monitor project progress, identify potential risks, and proactively resolve issues that could impact schedule or quality. • Lead SCCAF coordination meetings, document action items, and ensure timely follow-through from all stakeholders. • Facilitate resolution of technical and data-related challenges, including equipment information, field discrepancies, and design revisions. • Manage the SCCAF process from project kickoff through final deliverables while maintaining accurate documentation and study records. • Support overall project operations, including invoicing coordination, document control, deliverable tracking, and quality assurance processes.

• Bridge the gap between unstructured, real-world data, and AI models • Structure clinical datasets • Write reproducible code • Enforce incoming data quality control • Design data dictionaries and ontologies • Participate in technical conversations with external partners • Translate ambiguous source data into harmonized, AI-ready assets • Map diverse clinical data to industry-standard biomedical ontologies • Design, build, and maintain data dictionaries, schemas, and metadata models • Establish, automate, and enforce data quality control frameworks • Write production-grade Python code for data cleaning and harmonization • Audit data to find missing variables, anomalies, and hidden biases • Utilize clinical data progression metrics

• Operate at the intersection of data engineering, clinical science, and partner collaboration across two strategic domains: • Technical conversations with external partners (hospitals, research institutions, CROs/CMOs) and dive into the details of diverse clinical data structures. • Translate ambiguous source data into harmonized, AI-ready assets. • Map and align diverse clinical data to industry-standard biomedical ontologies. • Design, build, and maintain data dictionaries, schemas, and metadata models. • Establish, automate, and enforce data quality control (QC) and validation frameworks for incoming partner data. • Write production-grade Python code to automate data cleaning and harmonization tasks. • Practical understanding of how clinical data is generated in the real world. • Identify anomalies and hidden biases in incoming data.

• Senior professional with strong analytical skills and business acumen, responsible for understanding processes, identifying value-creation opportunities, and translating complex challenges into analytical solutions. • Will act as a strategic bridge between business areas and the technical team, designing and prioritizing data-driven initiatives based on their potential to generate value. • Facilitation and immersion: lead meetings to gather requirements, map and model processes with clients; • Solution formulation: translate client needs and challenges into analytical approaches, defining modeling assumptions and the most suitable method; • Analytics liaison: translate business challenges for the data science team, prioritizing the highest-impact initiatives; • Storytelling and executive presentation: lead presentations to client senior management, turning complex data and BI reports into clear, actionable insights; • Strategy and value generation: define metrics (KPIs), build structured business cases, and quantify the financial/strategic return of proposed solutions.