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- Tasks: Lead AI and ML projects, ensuring smooth delivery and innovative solutions.
- Company: Join Moody's, a global leader in risk assessment and AI transformation.
- Benefits: Inclusive culture, competitive salary, and opportunities for professional growth.
- Why this job: Make an impact by turning risks into opportunities with cutting-edge AI technology.
- Qualifications: 5+ years in AI/ML delivery, Agile leadership, and strong communication skills.
- Other info: Diverse team environment with a focus on continuous learning and improvement.
The predicted salary is between 60000 - 80000 £ per year.
At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.
We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity.
Skills and Competencies- ML/GenAI Delivery in Enterprise: 5+ years of experience leading end-to-end delivery of AI/Machine Learning initiatives across complex environments
- Agile Leadership: Coaches Scrum/Kanban practices; drives ceremonies and continuous improvement
- Backlog & Execution: Builds, prioritizes, and manages backlogs; aligns scope, timeline, and quality across squads
- Stakeholder Communication: Delivers project status updates, manages dependencies/risks, and facilitates decisions
- Project Reporting & Governance: Maintains dashboards and documentation; enforces delivery standards and controls
- Tools: Jira, Confluence, Agile estimation (story points, velocity, burndown)
- Technical Fluency (Preferred): Working knowledge of data science workflows, coding concepts, AWS, and enterprise deployments
- Multi-Squad Coordination (Preferred): Experience scaling delivery across regions and cross-functional teams
- Familiarity with Machine Learning and GenAI tools and frameworks
- Good knowledge of finance concepts, notably financial analysis
- Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using AI tools to streamline workflows and enhance operational efficiency
- Proven ability to implement AI-powered solutions to solve business challenges
- Bachelor’s or master’s degree in computer science, engineering, or a related field is preferred. Candidates with business-related degrees will also be considered, provided they have prior hands-on technical experience
- Professional certifications such as PMP (Project Management Professional), AWS Certified Cloud Practitioner, or equivalent delivery/Agile certifications (e.g., SAFe, Scrum Master) are highly desirable
- Oversee planning, execution, and release of multiple ML/Gen AI projects aligned with strategic objectives
- Manage dependencies across internal and external squads, ensuring smooth progress and timely delivery of product increments
- Facilitate quarterly planning and roadmap alignment with engineering and product teams
- Champion Agile methodologies (Scrum, Kanban) and coach cross-functional teams to embed Agile mindsets
- Facilitate ceremonies, retrospectives, and workshops to foster adaptability and innovation
- Engage with senior stakeholders across the organization, including analytical and technology teams
- Ensure transparency through dashboards, objectives and key results, and performance reporting
- Assist with running product pilot programmes, product rollouts, user feedback collection in the product management cycle
- Identify and mitigate delivery risks proactively
- Track quality metrics and drive continuous improvement
- Partner with data science, ML operations, and front-end teams to optimise release processes and reduce time-to-market
- Ensure alignment of delivery with product vision and business strategy
About The Team: Moody’s Ratings’ AI Analytics group develops advanced ML/GenAI for high-profile data science initiatives. The successful candidate will guide teams in building robust, scalable, and secure ML/Gen AI solutions. The successful candidate will strive to meet Moody’s values: openness, diversity, inclusivity, respect, and a willingness to learn. Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.
Senior Business Analyst - AI Enablement employer: Moody's Investors Service
Contact Detail:
Moody's Investors Service Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Business Analyst - AI Enablement
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Moody's on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by diving deep into AI and machine learning trends. Show us that you're not just familiar with the basics but are genuinely excited about how these technologies can transform business.
✨Tip Number 3
Practice your storytelling skills! Be ready to share specific examples of how you've led projects or solved complex problems in the past. We love hearing about real experiences that showcase your skills.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows us you’re serious about joining the Moody's team.
We think you need these skills to ace Senior Business Analyst - AI Enablement
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Business Analyst role. Highlight your experience in AI/Machine Learning initiatives and Agile methodologies to catch our eye!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're excited about this opportunity at Moody's. Share specific examples of how you've turned risks into opportunities in your past roles—this is your chance to shine!
Showcase Your Technical Skills: Don’t forget to mention your technical fluency! If you’ve got hands-on experience with AI tools or data science workflows, let us know. We love seeing candidates who can bridge the gap between tech and business.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting role. Don’t hesitate—apply today!
How to prepare for a job interview at Moody's Investors Service
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI and machine learning concepts. Be ready to discuss how you've implemented AI solutions in past projects, as well as any tools or frameworks you're familiar with. This will show that you can not only talk the talk but also walk the walk.
✨Showcase Your Agile Experience
Since the role involves championing Agile methodologies, be prepared to share specific examples of how you've led Scrum or Kanban practices in previous roles. Highlight your experience in managing backlogs and facilitating ceremonies, as this will demonstrate your ability to drive continuous improvement.
✨Communicate Like a Pro
Effective stakeholder communication is key for this position. Practice articulating project updates, managing dependencies, and discussing risks clearly and concisely. You might even want to prepare a few scenarios where you successfully navigated complex stakeholder relationships.
✨Embrace Moody's Values
Familiarise yourself with Moody's core values: openness, diversity, inclusivity, respect, and a willingness to learn. Think of examples from your past experiences that align with these values, as demonstrating cultural fit can be just as important as technical skills.