• Define and own Perci’s data strategy, roadmap, and governance framework, ensuring data is treated as a core organisational asset • Build and lead a high-performing data team — including data engineers, analysts, and data scientists — scaling the function in line with business growth • Establish and maintain robust, scalable data infrastructure and pipelines that support both clinical and commercial needs • Partner closely with the clinical, product, and commercial teams to translate data into actionable insights that drive better patient outcomes and business performance • Lead on data governance, privacy, and compliance — including GDPR, NHS Data Security Standards, and other relevant healthcare regulations • Develop and own our approach to clinical data and real-world evidence, enabling Perci to demonstrate impact and support research partnerships • Drive the adoption of data-driven decision-making across the organisation, supporting a culture of measurement, experimentation, and learning • Work with the CTO and leadership team to define key metrics, build reporting infrastructure, and provide board-level data visibility • Identify and evaluate opportunities to leverage AI and machine learning to enhance Perci’s clinical and operational capabilities • Represent data at the leadership level, contributing to fundraising narratives, investor reporting, and due diligence processes

• Lead end-to-end delivery of a large-scale AI data center campus. • Oversee the full construction lifecycle — from pre-construction through commissioning and turnover — ensuring schedule, budget, quality, and safety targets are met. • Participate in constructability reviews, value engineering sessions, and design coordination meetings to ensure construction-ready documents and optimized project delivery. • Develop comprehensive construction execution plans including phasing strategies, logistics plans, site utilization layouts, and temporary facility requirements for the AI campus. • Lead the subcontractor procurement process including bid solicitation, scope leveling, bid analysis, contract negotiation, and subcontract award for all major trade packages. • Establish project-specific procedures for document control, RFI management, submittal processing, change order administration, and progress reporting. • Develop, manage, and maintain the detailed CPM construction schedule using Primavera P6 or Microsoft Project, integrating all disciplines, milestones, and long-lead procurement items. • Manage the project budget from notice-to-proceed through final closeout, tracking committed costs, actual expenditures, forecasted costs-to-complete, and projected final cost against the approved GMP or lump sum contract value. • Implement and enforce the project-specific quality management plan, ensuring all work meets the stringent quality standards required for mission-critical AI data center infrastructure.

Role Description Navarro Research and Engineering is recruiting a Senior Data Scientist / AI Engineer (3878). This is a remote position. Citizenship is required. We are seeking a Senior Data Scientist / AI Engineer to design, develop, deploy, and maintain machine learning and generative AI solutions within a government environment. This role will support both locally hosted AI systems and cloud-based AI services within Microsoft Azure Government, including Azure AI Foundry and related Azure AI services. The ideal candidate has hands-on experience building production AI systems, deploying and operating open-source large language models (LLMs), implementing secure MLOps practices, and developing AI applications that meet government security and compliance requirements. Qualifications - Bachelor's degree in Data Science, Computer Science, Engineering, Mathematics, Statistics, or related field. - Master's degree preferred. - 5+ years of experience in data science, machine learning, AI engineering, or related fields. - 2+ years of experience deploying and operating production AI/ML systems. - Experience supporting secure government, defense, or regulated environments preferred. Requirements - Strong knowledge of supervised and unsupervised learning techniques. - Experience with model development, evaluation, and optimization. - Statistical analysis and experimental design experience. - Proficiency in Python and common ML frameworks. - Experience deploying and operating open-source LLMs. - Experience with Azure AI Foundry, Azure Machine Learning, Azure OpenAI, Azure Kubernetes Service (AKS), Azure Storage and Data Services, Azure Identity and Access Management. - Experience with Docker, Kubernetes, GPU-based inference systems, vLLM, Ollama, TGI, or similar inference platforms. - Understanding of model quantization and performance optimization techniques. - Experience with SQL and relational databases, data warehousing concepts, ETL/ELT pipeline development, vector databases, and semantic search platforms. - Git-based development workflows, REST APIs and microservices, CI/CD pipelines, Infrastructure-as-Code concepts. Benefits - Health Care Plan (Medical, Dental & Vision) - Retirement Plan (401k) - Life Insurance (Basic, Voluntary & AD&D) - Paid Time Off (Vacation & Public Holidays) - Short Term & Long Term Disability Success Criteria Within the first 12 months, the selected candidate will: - Deploy and support production AI solutions in Azure Government. - Establish repeatable MLOps processes for AI model deployment and maintenance. - Deploy and manage secure local/open-source LLM environments. - Develop mission-focused AI applications leveraging RAG and agentic workflows. - Improve operational efficiency through automation and advanced analytics. Due to the nature of the government contract requirements and/or clearances requirements, US citizenship is required. Navarro is an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, race, religion, color, national origin, age, disability, veteran’s status, or any classification protected by applicable state or local law. EEO Employer/Vet/Disabled

• Own and evolve Comfrt’s measurement framework alongside partners across MMM & MTA (Northbeam), incrementality (Workmagic), and experimentation • Lead Marketing Mix Modeling (MMM) initiatives in partnership with measurement partners and internal stakeholders • Design and evaluate geo tests, holdouts, lift studies, and quasi-experimental frameworks • Quantify true incremental impact across marketing channels, campaigns, creators, and growth initiatives • Identify saturation points, diminishing returns, and marginal efficiency curves across paid and organic channels • Continuously improve model accuracy, interpretability, and decision-making reliability • Develop models and analytical frameworks that improve CAC efficiency, LTV forecasting, contribution margin visibility, and retention economics • Analyze customer cohorts to identify drivers of high-value and durable customer behavior • Partner with Growth and Finance teams on forecasting, budget allocation, and investment planning • Help distinguish short-term performance gains from long-term brand and customer value creation • Build frameworks that measure the relationship between acquisition strategy, retention quality, and enterprise value creation • Build scalable analytical systems and production-grade models using Python and SQL • Partner with Data Engineering & Data Analytics & Insights to improve data quality, metric governance, and experimentation infrastructure • Standardize and maintain trusted business metrics including CAC, LTV, MER, contribution margin, retention, and incremental ROI • Collaborate with Engineering and BI teams to operationalize models into dashboards, workflows, and reporting systems • Ensure measurement systems remain scalable, reliable, and actionable as the business grows • Translate complex analyses and modeling outputs into clear, actionable business recommendations • Influence executive decision-making around growth investments, profitability, and long-term business quality • Partner cross-functionally across Growth, Finance, Product, Data Engineering and Technology teams. • Help establish a culture of rigorous, data-informed decision-making across Comfrt