Manager I
AIM.GEN.M1
Focuses on execution and team management, leading the design, development, and deployment of AI and machine learning solutions to address key R&D challenges.
Focuses on execution and team management, leading the design, development, and deployment of AI and machine learning solutions to address key R&D challenges.
The story of this role
Who does this work
An Artificial Intelligence Manager who is passionate about leveraging AI to transform biotechnology and life sciences research, aiming to make significant contributions in drug discovery and clinical diagnostics.
The problem this role solves
- The external problem: The rapid pace of scientific discovery and the overwhelming complexity of biological data make it challenging to implement effective AI/ML solutions.
- The internal problem: They struggle with the pressure of delivering innovative solutions while ensuring alignment with ethical standards and regulatory frameworks.
- Why it matters: They believe that the intersection of AI and biotech should ultimately improve human health and quality of life, and feel frustrated when technological advancements don’t translate into real-world benefits.
The plan
- Assess existing AI/ML capabilities and identify gaps in current biotech research workflows.
- Develop a strategic roadmap for AI integration in collaboration with cross-functional teams.
- Implement AI solutions with an emphasis on regulatory compliance and ethical considerations.
- Train and mentor team members on AI technologies and foster a culture of innovation.
- Monitor outcomes and iterate on AI deployments to ensure they meet the evolving needs of scientific research.
What's at stake
Inability to effectively utilize AI technologies, resulting in missed research opportunities. Failure to comply with regulatory standards leading to potential legal and ethical repercussions. Loss of stakeholder trust due to ineffective AI implementations that do not yield real-world results.
Success looks like
Accelerating the pace of drug discovery by reducing time to market for new therapies. Enhancing the accuracy of clinical diagnostics, leading to better patient outcomes. Fostering a culture of continuous improvement and innovation within the organization.
Summary
Focuses on execution and team management, leading the design, development, and deployment of AI and machine learning solutions to address key R&D challenges.
Level — M1 — Manager (Team Lead)
Front-line people manager of a single team; owns delivery, coaching, and execution.
- Scope
- A single team
- Autonomy
- Manages within established goals
- Complexity
- Day-to-day delivery and people issues
- Impact
- Team output and health
- Decision rights
- Owns team execution, hiring input, performance
- Leadership
- Direct people management of one team
- Typical experience
- 3–6 yrs
Core outputs
No core outputs recorded yet.
Adjacent roles
Nearest roles by structural coordinates (level + taxonomy). Distance 0 → 1; each carries its 3-state match band. How coordinates work → · Compare side-by-side →
Componentsshow ▾
Responsibilities3
- Lead the design, development, and deployment of AI and machine learning solutionscommonlevel
- Make architectural and technology stack decisions for AI systemscommonlevel
- Manage a team of AI/ML engineers, data scientists, and analystscommonlevel
Tasks5
- Design AI solutions.commonlevel
- Develop machine learning models.commonlevel
- Deploy AI systems.commonlevel
- Manage project timelines.commonlevel
- Mentor team members.commonlevel
Skills8
- AI system designcommonlevel
- Machine learning deploymentcommonlevel
- Team leadershipcommonlevel
- Technical architecturecommonlevel
- Project managementcommonlevel
- Data analysiscommonlevel
- Problem-solvingcommonlevel
- Communicationcommonlevel
Knowledge8
- AI/ML algorithmscommonlevel
- Technology stack architecturecommonlevel
- Team management principlescommonlevel
- Data science methodologiescommonlevel
- R&D processescommonlevel
- Biotech applicationscommonlevel
- Software development lifecyclecommonlevel
- Innovation in AIcommonlevel
competency3
- AI/ML Solution Developmentcommonlevel
- Technical Leadership & Architecturecommonlevel
- Team Management & Mentorshipcommonlevel
qualification3
- 5+ years of total work experience in data science/AIcommonlevel
- Deep knowledge of machine learning algorithmscommonlevel
- Master’s or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Bioinformatics, Computational Biology, or a related STEM fieldcommonlevel
Title aliasesshow ▾
| Alias | Type | Confidence | Approved |
|---|---|---|---|
| Manager, Artificial Intelligence Manager | common | medium0.66 | — |
| Artificial Intelligence Manager Manager | common | medium0.60 | — |
| Manager, Drug Discovery | common | medium0.66 | — |
| Drug Discovery Manager | common | medium0.60 | — |
| Manager, Genomics | common | medium0.66 | — |
| Genomics Manager | common | medium0.60 | — |
| Manager, Clinical Diagnostics | common | medium0.66 | — |
| Clinical Diagnostics Manager | common | medium0.60 | — |
| Manager, Bioinformatics | common | medium0.66 | — |
| Bioinformatics Manager | common | medium0.60 | — |
| Manager I | common | medium0.50 | — |
Classification mappingsshow ▾
O*NET / SOC
- code=15-0000title=Computer & Mathematical Occupationssource=inferred_from_superfunctionreviewStatus=needs_review