Scrum Master

Scrum Master

Key Responsibilities:

• Lead and facilitate

  Scrum ceremonies

  : sprint planning, daily stand-ups, sprint reviews, retrospectives, and backlog grooming.
• Guide Agile teams working on

  AI/ML model development, data platform integration

  , and

  automation initiatives

  in finance.
• Act as a bridge between

  technical teams

  (engineers, architects, data scientists) and

  business stakeholders

  to maintain alignment.
• Track team performance and delivery timelines through

  JIRA, Azure DevOps

  , or similar tools.
• Identify and remove project impediments, resolve conflicts, and coach the team on Agile best practices.
• Collaborate with the Product Owner to ensure backlog items are well defined and prioritized based on value delivery.
• Facilitate

  PI planning, sprint metrics tracking

  , and delivery forecasting in a

  SAFe or hybrid Agile environment

  .

Required Qualifications:

• 7+ years of total experience

  , including

  5+ years as a Scrum Master

  in Agile/Scrum environments.
• Proven experience managing

  AI/ML-related projects

  involving model training, validation, and deployment.
• Strong domain knowledge of

  BFSI

  , especially

  Wealth and Asset Management

  ,

  Retail Banking

  , or

  Investment Platforms

  .
• Hands-on experience working with

  cross-functional Agile teams

  , preferably in product-based or financial enterprise environments.
• Strong knowledge of

  Agile frameworks

  (Scrum, SAFe), Agile metrics, and Agile maturity assessments.
• Experience with tools like

  JIRA, Confluence, Azure DevOps

  , or similar.
• Solid technical understanding of

  AI workflows, data platforms, APIs

  , and

  cloud-based environments (AWS, GCP, or Azure)

  .
• Excellent communication and stakeholder management skills.
• Scrum Master Certification (

  CSM, PSM I/II

  ) preferred.
• Prior experience in

  AI risk, governance, or model compliance

  is a strong plus.

Preferred Skills:

• Experience supporting multiple agile squads across geographies.
• Strong familiarity with

  regulatory environments

  (e.g., SEC, FINRA, GDPR) as applied to AI/ML projects.
• Experience working with

  data teams

  , including MLOps or analytics teams in BFSI contexts.