Associate Director, Information Systems
RemoteUnited States
Job Summary
Lead the strategy, delivery, and continuous evolution of a portfolio supporting Coverage Pricing Intelligence, CapAI, and Pricing capabilities by partnering with business leaders and engineering teams to define strategic roadmaps. Drive execution through PI Planning, backlog refinement, and sprint planning while establishing OKRs to monitor predictability, flow, and business value. Manage platform operations including production support, incident management, and root cause analysis to ensure operational stability. Leverage data-driven decision-making to prioritize investments and accelerate AI and advanced analytics initiatives using modern data platforms and machine learning.
Required Qualifications
- Doctorate degree and 3 years of Information Systems experience
- Master's degree and 7 years of Information Systems experience
- Bachelor's degree and 9 years of Information Systems experience
- Associate's degree and 12 years of Information Systems experience
- High school diploma / GED and 14 years of Information Systems experience
- Minimum of 3 years' experience directly managing people
- Leadership experience leading teams, projects, programs, or directing the allocation or resources
Desired Qualifications
- Experience leading enterprise technology products or platforms supporting analytics, pricing, commercial operations, business intelligence, or AI-enabled business capabilities
- Strong technical understanding of modern data and analytics platforms, including Databricks, Python, SQL, Apache Spark, cloud-native data engineering architectures, and scalable data pipelines
- Experience delivering scalable cloud-based technology solutions on AWS, including analytics platforms, data pipelines, machine learning workloads, application security, and operational monitoring
- Experience delivering data science, machine learning, and AI-powered products from concept through production deployment, business adoption, and continuous improvement
- Understanding of Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, prompt engineering, model orchestration, evaluation frameworks, and responsible AI practices
- Experience managing the complete product lifecycle, including product strategy, roadmap development, prioritization, delivery, platform operations, adoption, and continuous improvement
- Demonstrated ability to translate complex technical concepts into product strategies, investment recommendations, and measurable business outcomes for technical and non-technical stakeholders
- Experience leading multidisciplinary product teams consisting of Product Owners, Data Engineers, Software Engineers, Data Scientists, Machine Learning Engineers, Architects, Business Analysts, and Quality Engineers
- Strong understanding of enterprise data architecture, governance, security, privacy, and regulatory requirements, preferably within the pharmaceutical, healthcare, life sciences, or another highly regulated industry
- Technical fluency to evaluate solution designs, guide architectural decisions, identify delivery risks, and effectively partner with engineering organizations without requiring day-to-day hands-on software development
- Proven ability to influence business and technology stakeholders, build trusted partnerships, and drive alignment across cross-functional teams
- Experience working in Agile product organizations using SAFe methodologies and driving continuous improvement across product delivery teams
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