Jobs at LOGEX International Healthcare Analytics B.V.

Support HR dashboards, reporting, and workforce analyses; assist compensation benchmarking and salary processes; maintain HRIS reporting and data quality; support HR system testing and M&A integrations; experiment with AI/automation in HR; act as first point of contact for HR data questions while working with senior HR, Finance, and IT stakeholders.

Define and deliver AI strategy, architecture, and standards. Design production-ready solutions (retrieval, orchestration, model serving, evaluation). Implement MLOps/LLMOps, governance, compliance (GDPR), and embed AI into products working with product, engineering, data, and platform teams.

Operate and develop cloud-native infrastructure for a healthcare analytics platform. Build and run CI/CD pipelines, deploy applications across multi-cloud Kubernetes clusters, automate and optimize processes, troubleshoot cloud/network/app issues, and collaborate with development teams to introduce new solutions and technologies.

Drive new business and expand existing enterprise and public-sector accounts across DACH for a healthcare financial analytics SaaS. Engage C‑level stakeholders, navigate public procurement and tenders, manage long sales cycles, onboard clients with internal teams, identify upsell opportunities, and represent LOGEX at events and HQ meetings.

Own and prioritise the clinical intelligence roadmap, build and harmonise pan-European clinical data assets (classifications, benchmarks, mappings), onboard new data sources, apply AI for extraction and quality, maintain the RWE common data model, and establish governance to support Provider Analytics and Real-World Data products.

Build and ship in-product AI capabilities: integrate LLMs and RAG, design prompting and evaluation, implement MLOps/LLMOps, ensure production reliability, privacy, and compliance, and collaborate with data, platform and product teams to move AI from prototype to production.

Design, build, and maintain Snowflake-based data models and pipelines, transform data into business-ready datasets and marts, ensure data quality and governance, and support Power BI reporting while collaborating with stakeholders and data teams.

Define and evolve the enterprise data architecture and roadmap, set standards for modelling, integration, interoperability and storage, embed governance, lineage, security and compliance, support analytics and AI, provide technical leadership and reviews, evaluate tooling, and drive integration of acquired businesses to reduce fragmentation and technical debt.

Design, build, and maintain the internal data warehouse and scalable data pipelines. Integrate data from multiple sources, develop and maintain Snowflake data models, configure Workato integrations, ensure data quality and performance, make data accessible for reporting and analytics, and contribute to DWH architecture and best practices while collaborating with stakeholders.