At a Glance
- Tasks: Lead exciting AI projects and drive innovation in a collaborative environment.
- Company: Join Moody's, a global leader in risk assessment and AI transformation.
- Benefits: Inclusive culture, competitive salary, and opportunities for professional growth.
- Other info: Dynamic team focused on diversity, learning, and continuous improvement.
- Why this job: Make a real impact by turning risks into opportunities with cutting-edge AI solutions.
- Qualifications: 5+ years in AI/Machine Learning project management and Agile methodologies.
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.
If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. 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.
Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.
Let's begin! Project Manager - AI Enablement in London employer: Moody's
Moody's is an exceptional employer that fosters an inclusive and innovative work culture, where every employee is encouraged to express their ideas and contribute to meaningful projects. With a strong focus on professional growth, employees have access to diverse training opportunities and the chance to work alongside industry leaders in catastrophe risk management. Located in a vibrant environment, Moody's not only prioritises employee well-being but also champions diversity, making it a rewarding place for those looking to make a significant impact in their careers.
StudySmarter Expert Advice🤫
We think this is how you could land Let's begin! Project Manager - AI Enablement in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Moody's or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Moody's.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Moody's.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Moody's that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Let's begin! Project Manager - AI Enablement in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Moody's.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Moody's and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Moody's
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Moody's uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
