ROLES & RESPONSIBILITIES
Responsibilities will include, but are not limited to
People leadership and line management: coaching, performance management, hiring input, workload prioritization, team health, and talent development.
Technical leadership and cross-functional delivery: Guide data scientists, product owners, business partners, architecture teams, AI platform teams, data teams, and stakeholders through delivery decisions, dependencies, and tradeoffs.
Product ownership, domain translation, and client success: Partner with subject-matter experts, business stakeholders, and technical teams to translate supply chain needs into scalable product solutions that deliver measurable outcomes.
Data science and data engineering fluency: applying core principles of artificial intelligence, machine learning, data modeling, data quality, metadata, data lineage, and data pipelines to define solutions to complex problems.
AI engineering and application delivery: building, integrating, evaluating, and operationalizing AI/ML capabilities, including context engineering, agents/workflows, evaluations, guardrails, and human-centric designs.
Learning agility and hands-on technical credibility: demonstrating leading-edge understanding of AI, semantic technologies, and product practices while retaining enough technical depth to prototype, review designs, challenge assumptions, and unblock teams.
Pragmatic prioritization and delivery management: balancing business needs, technical debt, delivery capacity, risk, speed, dependencies, stakeholder expectations, and long-term scalability across multiple projects.
Enterprise architecture, quality, and compliance leadership: ensuring solutions are secure, reliable, maintainable, well-documented, and aligned with enterprise architecture, operational standards, cybersecurity, data privacy, model governance, GxP, HIPAA, and other applicable life sciences compliance expectations.
Innovation and engineering culture: fostering a culture of innovation, accountability, inclusion, continuous learning, technical curiosity, rapid prototyping, platform-first thinking, and high-quality delivery.
FUNCTIONAL SKILLS
Must-Have Skills
Experience in pharma, biotechnology, life sciences, regulated manufacturing, or GxP-compliant technology environments with quality, compliance, data privacy, security, and documentation expectations.
Strong understanding of supply chain processes.
Demonstrated experience leading software engineering, AI engineering, data engineering, analytics, or technical delivery teams.
Experience operating in product, platform, data, analytics, or enterprise application environments.
Ability to translate business needs into scalable, secure, maintainable, and compliant technology solutions.
Experience operating in Agile delivery environments and managing multiple priorities, projects, and stakeholder groups.
Experience supporting end-to-end software delivery from concept through production stabilization and ongoing support.
Ability to assess technology options, understand tradeoffs, and make sound recommendations based on business value, cost, risk, compliance, technical debt, delivery capacity, and long-term impact.
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