Scrum Master (AI/ML)

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💎 Seniority level: Senior, 5+ years

📍 Location: United States of America

🔍 Industry: Software Development

🏢 Company: spgi_careers

🗣️ Languages: English

⏳ Experience: 5+ years

🪄 Skills: LeadershipAgileArtificial IntelligenceMachine LearningSCRUMData scienceCommunication SkillsCollaborationProblem SolvingAgile methodologiesMentoringCoachingExcellent communication skillsTeamworkCross-functional collaborationRisk ManagementStakeholder managementData modelingData analyticsData management

Requirements:

5+ years of experience leading teams as a Scrum Master, including experience working with AI, Data Science, or ML-focused teams.
Familiarity with Agile challenges unique to AI/ML, such as model experimentation cycles, data dependencies, and deployment hurdles.
Excellent communication and collaboration skills
Strong facilitation skills, especially in research-driven and data-centric teams
Demonstrated ability to identify and mitigate risks and impediments
Team-first, servant leader mentality

Responsibilities:

Act as a servant leader and agile coach, guiding AI, Data Science, and ML teams on agile values, principles, and practices while balancing research-driven workflows with iterative delivery.
Facilitate Scrum events including Daily Stand-ups, Iteration Planning, Refinement sessions, Iteration Reviews, and Retrospectives, ensuring they are tailored to the unique needs of AI/ML teams, such as managing research spikes, data dependencies, and model iteration cycles.
Manage risks, dependencies, and remove impediments, particularly those unique to AI/ML development, such as data availability, computational constraints, and alignment between research and engineering teams.
Partner with global stakeholders, Product Owners, Data Scientists, and ML Engineers to align priorities, ensure the readiness of AI/ML features, and enable the team to deliver high-quality models and insights that align with business objectives.
Promote a culture of continuous improvement and learning, encouraging experimentation while ensuring teams have structured feedback loops to validate AI/ML solutions before full deployment.
Collaborate with peer Scrum Masters, RTEs, and technical leaders to share knowledge, refine agile processes for AI/ML teams, and drive agile maturity across the organization.
Foster transparency and trust by clearly communicating team progress, challenges, and successes to stakeholders, ensuring alignment across business, engineering, and data science teams.

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