Description
You will lead the AIN-based data science organization that builds and operates scientific computational, data, and AI/ML pipelines and workflows for Amgen Research. You will operate across India/EU/US (Eastern, Central, Pacific) time zones and coordinate outcomes across the ARIA, Global Research, ATMOS Tech, and ATMOS AI&D. You will own portfolio outcomes across the Research data ecosystem, AI/ML for research, and high-performance computing enablement, ensuring robust, resilient pipelines and reliable, scalable services.
**Core Responsibilities**
+ Set multi-year strategy, organization design, and investment roadmap for research compute & AI platforms.
+ Establish standards and promote methods for robust, resilient computational and data science pipelines; drive adoption and measure cycle-time impact.
+ Govern capacity, cost, and quality: quotas, GPU utilization, $/compute-hour, and SLA attainment.
+ Partner on schemas, vocabularies, lineage, and compliance with Reseach data stewards.
+ Coordinate instrument onboarding and lab software integrations with RA&T.
+ Mentor and grow L5/L4 engineers; develop on-call rotations and technical leadership bench.
**Core Competencies**
+ Enterprise strategy, product/platform thinking, and financial acumen.
+ Global change leadership; cross-cultural communication across time zones.
+ Platform engineering literacy: containers/Kubernetes; workflow orchestration (Nextflow/Airflow/Argo/Prefect).
+ Compute literacy: HPC schedulers (Slurm) and/or distributed compute (Spark/Ray/Databricks).
+ Data governance literacy: schemas, vocabularies, lineage, and compliance.
+ Executive communication; stakeholder management across science, engineering, and operations.
**Qualifications**
+ Basic: Bachelor’s degree required; advanced degree (MSc/PhD) preferred
+ Scientific literacy: Training and experience in chemistry, biology, or related scientific fields
+ Domain literacy: Familiarity with R&D domains (biology, chemistry, protein science, computational sciences) and experience partnering closely with scientists.
+ Technical literacy: Python plus one of Java/Scala/C++; containers/Kubernetes; workflow orchestration; HPC schedulers; distributed compute; data lakehouse; CI/CD
+ Experience: 18–24 years in platform/software/data leadership with cross‑region operations; budget/vendor management; policy/standards influence
