Director Data AI & Analytics

Responsibilities

• Define the multi-year Data/AI roadmap for locations in California and Wisconsin; align to business priorities and compliance needs.
• Stand up a Data, AI & Analytics Center of Excellence with domain-aligned product squads (M&Q, R&D/Bioinformatics, Finance/SC).
• Run governance: Data & AI Steering Committee, Model Risk & Compliance Board; assign data product ownership.
• Own the enterprise data platform (lakehouse/warehouse), ingestion (ELT/CDC), orchestration, and semantic/metric layers.
• Implement catalog/lineage, data quality rules, access controls; drive data product SLAs and ownership.
• Integrate core systems: MES (e.g., PAS-X), QMS (ETQ/Veeva), LIMS/ELN (LabWare/Benchling), ERP (e.g., SAP/Oracle), OSI PI/AVEVA, and instrument data hubs.
• Deliver executive and operational analytics (FPY/yield, OEE, deviation/CAPA TAT, batch release, QC throughput, inventory turns, cost-to-serve).
• Enable governed self-service (certified datasets/semantic models, KPI library, training, community of practice).
• Lead data science programs for manufacturing quality, supply chain, and R&D.
• Own bioinformatics analytics and pipelines (e.g., NGS/omics workflows, imaging pipelines, assay analytics) and integration with lab systems and data platforms.
• Build responsible and agentic AI capabilities (assistants/co-pilots, retrieval/grounding, task automation) with MLOps (experiment tracking, model registry, CI/CD, monitoring, retraining).
• Separate GxP vs non-GxP AI; ensure intended use, explainability, validation/CSA, and periodic review for regulated models.
• Embed compliance by design: 21 CFR Part 11, Annex 11, ALCOA+, data retention/archival, audit trails.
• Partner with QA/CSV on risk-based validation, test evidence, and inspections; maintain validated state for applicable analytics/data flows.
• Cook with Corporate Security on classification, RBAC/least privilege, encryption, logging/monitoring, and incident response for data/AI workloads.
• Govern AI safety: model cards, red-team testing, bias/fairness checks, PHI/PII safeguards, vendor due diligence.
• Prioritize a portfolio of use cases with quantified value; pilot, scale winners, retire low-value work.
• Publish a quarterly “Data & AI Outcomes” report (business impact, adoption, cost/performance, compliance posture).
• Select and govern platform vendors (cloud, data/ML, BI, bioinformatics tools) and SIs; negotiate commercials, SLAs, exit terms.
• Drive FinOps: usage visibility, rightsizing, tiered storage, and cost/performance optimization.
• Hire and develop data/platform/analytics engineers, data scientists/ML engineers, bioinformatics engineers, and product managers.
• Build cross-site career paths and a culture of reliability, compliance, and measurable impact.

  Requirements

  • BS/BA (or equivalent) in Business, Computer Science, Data Science or Bioinformatics or similar.
  • 10+ years leading Data/Analytics functions with 5+ years in regulated life sciences (biotech, pharma, CDMO); multi-site/global experience.
  • Demonstrated people management experience, including building, mentoring, and leading high-performing teams.
  • Ownership of enterprise data platforms (lakehouse/warehouse), analytics programs, and MLOps in production.
  • Strong GxP/CSV/CSA knowledge with practical application in analytics/AI and data flows; 21 CFR Part 11/Annex 11/ALCOA+.
  • Hands-on familiarity with bioinformatics analytics/pipelines (e.g., NGS/omics, imaging, workflow orchestration) and integration with LIMS/ELN and lab systems.
  • Proven record converting Data/AI programs into business outcomes (e.g., cycle time, yield/FPY, cost, quality).
  • Cross-functional leadership with QA/CSV, Manufacturing/Quality, R&D, Security, ERP/MES/QMS owners, and vendors.
  • Excellent executive communication and pragmatic technical guidance.
  • Platforms: Databricks/Snowflake/BigQuery; Azure/AWS data services; Spark; DBT; Airflow/Prefect; Kafka/EventHub.
  • Bi: Power BI/Tableau; semantic/metrics layers; KPI governance.
  • MLOps/AI: MLflow/W&B, SageMaker/Azure ML; vector DBs/RAG; LLM orchestration; agent frameworks; feature stores.
  • Bioinformatics: Nextflow/Snakemake, CWL/WDL; common tools (e.g., GATK) or imaging/omics pipelines; HPC/containers.
  • Governance: Collibra/Alation/Atlan; model risk management/AI governance.
  • Certifications: GAMP 5/CSA, ITIL, cloud (Azure/AWS), or data governance certifications.
  • Ability to speak, read, and write in English.
  • Good verbal and written communication skills; effective presentation skills.

    Qualifications

    • BS/BA (or equivalent) in Business, Computer Science, Data Science or Bioinformatics or similar.
    • 10+ years leading Data/Analytics functions with 5+ years in regulated life sciences (biotech, pharma, CDMO); multi-site/global experience.
    • BS/BA (or equivalent) in Business, Computer Science, Data Science or Bioinformatics or similar.
    • Strong GxP/CSV/CSA knowledge with practical application in analytics/AI and data flows; 21 CFR Part 11/Annex 11/ALCOA+.
    • Hands-on familiarity with bioinformatics analytics/pipelines (e.g., NGS/omics, imaging, workflow orchestration) and integration with LIMS/ELN and lab systems.
    • Proven record converting Data/AI programs into business outcomes (e.g., cycle time, yield/FPY, cost, quality).
    • Cross-functional leadership with QA/CSV, Manufacturing/Quality, R&D, Security, ERP/MES/QMS owners, and vendors.
    • Excellent executive communication and pragmatic technical guidance.
    • Platforms: Databricks/Snowflake/BigQuery; Azure/AWS data services; Spark; DBT; Airflow/Prefect; Kafka/EventHub.
    • Bi: Power BI/Tableau; semantic/metrics layers; KPI governance.
    • MLOps/AI: MLflow/W&B, SageMaker/Azure ML; vector DBs/RAG; LLM orchestration; agent frameworks; feature stores.
    • Bioinformatics: Nextflow/Snakemake, CWL/WDL; common tools (e.g., GATK) or imaging/omics pipelines; HPC/containers.
    • Governance: Collibra/Alation/Atlan; model risk management/AI governance.
    • Certifications: GAMP 5/CSA, ITIL, cloud (Azure/AWS), or data governance certifications.
    • Ability to speak, read, and write in English.
    • Good verbal and written communication skills; effective presentation skills.

      Skills

      • BS/BA (or equivalent) in Business, Computer Science, Data Science or Bioinformatics or similar.
      • 10+ years leading Data/Analytics functions with 5+ years in regulated life sciences (biotech, pharma, CDMO); multi-site/global experience.
      • BS/BA (or equivalent) in Business, Computer Science, Data Science or Bioinformatics or similar.
      • Strong GxP/CSV/CSA knowledge with practical application in analytics/AI and data flows; 21 CFR Part 11/Annex 11/ALCOA+.
      • Hands-on familiarity with bioinformatics analytics/pipelines (e.g., NGS/omics, imaging, workflow orchestration) and integration with LIMS/ELN and lab systems.
      • Proven record converting Data/AI programs into business outcomes (e.g., cycle time, yield/FPY, cost, quality).
      • Cross-functional leadership with QA/CSV, Manufacturing/Quality, R&D, Security, ERP/MES/QMS owners, and vendors.
      • Excellent executive communication and pragmatic technical guidance.
      • Platforms: Databricks/Snowflake/BigQuery; Azure/AWS data services; Spark; DBT; Airflow/Prefect; Kafka/EventHub.
      • Bi: Power BI/Tableau; semantic/metrics layers; KPI governance.
      • MLOps/AI: MLflow/W&B, SageMaker/Azure ML; vector DBs/RAG; LLM orchestration; agent frameworks; feature stores.
      • Bioinformatics: Nextflow/Snakemake, CWL/WDL; common tools (e.g., GATK) or imaging/omics pipelines; HPC/containers.
      • Governance: Collibra/Alation/Atlan; model risk management/AI governance.
      • Certifications: GAMP 5/CSA, ITIL, cloud (Azure/AWS), or data governance certifications.
      • Ability to speak, read, and write in English.
      • Good verbal and written communication skills; effective presentation skills.

        Benefits

        • Medical
        • Dental
        • Vision
        • Life Insurance
        • 401(k)
        • Paid Time Off

          Pay

          For California, the base salary range for this position is $154,565.00 - $216,100.