This role pays less than
62%
of similar roles. Most pay
$179,675–$262,600
— the shaded band above.
At the midpoint, this role pays about
$202k
versus about
$221k
for comparable roles.
Based on 240 similar postings.
Employer
About Amgen
Amgen is a leading biotechnology company that discovers, develops, manufactures, and delivers innovative human therapeutics, with products addressing conditions such as anemia, bone loss, inflammation, and cancer. Industry: Biotechnology & Pharmaceuticals
Amgen currently has
46 open roles
on FindRole.
Listed pay typically runs
$136,906–$184,235
across 44 roles with salary data.
Associate Director - Information Systems serves as the product leader for the Clinical Data Hub within the Clinical Design and Analysis organization. This role is responsible for establishing the product vision, multi-year roadmap, and investment priorities for a scalable clinical data foundation designed to facilitate discovery, integration, governance, and reuse of clinical development data. The individual will manage the product backlog, lead cross-functional teams, and oversee portfolio planning while ensuring regulatory compliance and platform reliability. Key technical competencies include experience with modern data architecture, cloud environments, data lakes, APIs, metadata, and DevOps. Preferred technologies include AWS, Databricks, Apache technologies, Python, R, SQL, Docker, and GitLab. The role addresses the critical challenge of accelerating study onboarding and improving data quality to enhance the speed and probability of successful product development and commercialization in a regulated environment.
Define and execute the strategic roadmap for the Clinical Data Hub to ensure scalable data foundation and integration.
Own and communicate the product vision, multi-year roadmap, investment priorities, and measurable outcomes to stakeholders.
Champion common data standards, metadata, governance, security, and interoperability to simplify data access across functions.
Manage the product portfolio by prioritizing the backlog, managing budgets, and making trade-off decisions on technical debt and compliance.
Provide people leadership for a cross-functional team to develop technical capabilities and foster a culture of accountability.
Execute workforce and resource strategies including talent development, succession planning, and vendor management.
Collaborate with infrastructure, security, and DevOps teams to deliver end-to-end value and dependable operations.
Represent the product in senior leadership forums to communicate progress, risks, and investment needs for the clinical data ecosystem.
What we're looking for
Must have one of: Doctorate with 4 years experience, Master's with 8 years, Bachelor's with 10 years, or Associate's with 12 years in Information Systems, Computer Science, or Biology.
High school diploma/GED holders must have at least 14 years of experience in Information Systems, Computer Science, or Biology.
Must have a minimum of 4 years of managerial experience managing people or leading teams, products, programs, or resource allocation.
Preferred knowledge of Clinical Development data, management processes, and regulated environments.
Preferred experience as a Product Manager or Owner for enterprise data, analytics, or platform products.
Preferred expertise in modern data architecture including cloud, data lakes, APIs, metadata, security, and DevOps.
Preferred proficiency with AWS, Databricks, Apache technologies, Python, R, SQL, Docker, and GitLab.
Must possess strong communication skills to build partnerships and present strategy to diverse stakeholders.
Remote (Thousand Oaks, CA)39 days ago
$171,556–$232,105
Databricks
Python
SQL
Apache Spark
AWS
Generative AI
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
Machine Learning
Agile
SAFe
Data Engineering
Analytics
Business Intelligence
Snowflake
Data Strategy
Data Governance
Metadata Management
Business Intelligence
Data Product Management
UAT
AI
Cloud Data Platforms
Data Quality
Source-to-Target Mapping
Analytics Enablement
AI
Machine Learning
Generative AI
Advanced Analytics
Python
R
Scala
Java
Databricks
AWS
Azure
MLOps
Causal Inference
Optimization
Predictive Modeling
Data Engineering
Model Governance
Machine Learning
Artificial Intelligence
Python
R
scikit-learn
PyTorch
Keras
Data Science
Statistics
SQL
Pandas
Deep Learning
Time Series Analysis
Data Visualization
Exploratory Data Analysis
Version Control
GenAI
NLP
Biostatistics