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Baylor Genetics

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501 - 1000 Mitarbeiter

Gegründet 1978

🧬 Biotechnologie

🔬 Wissenschaft

Biotechnology • Science

Baylor Genetics ist ein klinisches Genomik- und Präzisionsdiagnostiklabor in Zusammenarbeit mit dem Baylor College of Medicine, das umfassende genetische Tests und Interpretationsdienste anbietet. Das Unternehmen bietet Gesamtgenom- und Gesamt-Exom-Sequenzierungen, chromosomale Mikroarray-Analyse, Mitochondrientests, Pharmakogenomik und spezialisierte Tests an, zusammen mit genetischer Beratung, Unterstützung für Anbieter und Ressourcen für Versicherungen/Bezahlung. Baylor Genetics unterstützt Gesundheitsdienstleister, Forscher und Familien mit KI-gestützter Interpretation, multimodaler Datenintegration und End-to-End-Dienstleistungen im klinischen und Laborbereich.

Beschreibung

• Lead the design and execution of Baylor Genetics’ enterprise data and AI strategy • Establish a scalable data platform, enabling advanced analytics, and driving AI adoption across the organization • Build and lead a high-performing team while partnering across Technology, Genomic Sciences, Operations, and Commercial teams • Define and implement the enterprise data platform architecture (e.g., Databricks, Snowflake, Azure ecosystem) • Establish a single source of truth across clinical, operational, and financial data • Design scalable data ingestion, processing, and storage frameworks • Ensure interoperability across systems including LIMS, reporting platforms, and enterprise applications • Define and execute the company-wide AI strategy • Identify and prioritize high-value AI use cases (clinical, operational, customer-facing) • Lead development and deployment of AI/ML models and GenAI solutions • Establish governance for responsible AI (compliance, explainability, PHI protection) • Establish enterprise data governance framework (ownership, quality, lineage) • Ensure compliance with HIPAA, CAP, and other regulatory standards • Define data access, security, and retention policies • Partner closely with Security and Compliance teams • Build enterprise analytics capabilities to support decision-making • Standardize reporting and KPI definitions across the organization • Enable self-service analytics for business stakeholders • Build and lead the Data & AI organization (data engineering, data science, analytics) • Establish clear operating model and team structure • Mentor and develop technical and functional leaders • Partner with Product Engineering and Platform teams for execution alignment

🎯 Anforderungen

• 12+ years in data, analytics, or AI leadership roles • Proven experience building enterprise data platforms at scale • Experience leading AI/ML initiatives in production environments • Healthcare, life sciences, or regulated industry experience strongly preferred • Modern data platforms (Databricks, Snowflake, Azure, etc.) • Data engineering (ETL/ELT, streaming, pipelines) • Machine learning and AI frameworks • Data governance and security in regulated environments • Experience building and scaling high-performing teams • Strong executive communication skills • Ability to translate business needs into technical solutions • Track record of delivering measurable business impact

🏖️ Vorteile

• Health insurance • 401(k) matching • Flexible work hours • Paid time off • Remote work options