In A Nutshell
Lead the delivery of AI and data projects by managing defined workstreams, coordinating day-to-day activities, and ensuring smooth communication between internal teams and external stakeholders.
Responsibilities
- Work closely with senior project leads who provide strategic direction and oversight, while you focus on execution, organization, and ensuring tasks move forward as planned.
- Engage with clients to understand their needs, manage routine communication, and ensure updates and decisions are clearly documented.
- Collaborate with data scientists, engineers, and product owners to track timelines, anticipate risks, and escalate challenges early.
Skillset
- Project management: At least 3 years of experience managing defined workstreams within larger projects, including planning, task tracking, and coordinating delivery activities.
- Problem structuring and requirements gathering: Ability to ask critical questions that uncover clients underlying needs, gather the right inputs to clarify what success looks like, and contribute to developing structured scopes, requirements, and project documentation.
- Curiosity about AI driven problem solving: Genuine interest in how AI and data can be applied to real world challenges, with a learning mindset that supports engaging with technical teams and evolving solution areas.
- Client engagement: Ability to manage and own day to day client interactions, share routine updates, and support senior leads in expectation setting and decision making.
- Multi-stakeholder coordination: Experience coordinating across internal teams and external partners, ensuring quality delivery of outputs, while escalating alignment issues to senior leads when needed
- Communication: Strong verbal and written communication skills, with the ability to synthesize information clearly and present it in structured formats.
- Risk management: Ability to identify emerging risks or bottlenecks early and work with senior leads to address them.
- Leadership: Demonstrated ability to lead and work effectively with multidisciplinary teams, ensuring clarity on tasks, timelines, and dependencies.
- Agile ways of working: Familiarity with iterative delivery approaches that support continuous feedback and improvement.