Delivery Lead – AI Data Projects

Accountabilities •

Own end-to-end project delivery: Take accountability for a portfolio of AI data projects, ensuring data quality, delivery timelines, client satisfaction, unit economics, and gross margin targets are consistently achieved.

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Lead cross-functional teams: Coordinate project managers, engineers, researchers, data scientists, supply managers, product teams, and other specialists to maintain alignment and deliver successful outcomes.

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Manage project execution: Oversee project discovery, scope definition, planning, implementation, resource allocation, and adoption. Step in directly as a hands-on project manager when needed.

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Drive operational excellence: Establish and maintain effective delivery processes, communication practices, reporting standards, project status updates, retrospectives, and execution frameworks.

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Manage risks and resolve issues: Identify potential delivery challenges early, implement mitigation plans, remove blockers, and ensure stakeholders have clear visibility into progress and risks.

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Build strong client relationships: Serve as a trusted partner to clients and technical stakeholders, manage expectations, communicate progress transparently, and resolve issues to support satisfaction and long-term retention.

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Support business development: Collaborate with commercial teams to scope new opportunities, shape project proposals, define viable delivery models, and transition prospects into successful engagements.

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Optimize commercial performance: Balance delivery quality and customer outcomes with operational efficiency, resource utilization, unit economics, and profitability.

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Improve team performance: Motivate and support delivery teams, identify opportunities to improve workflows, and develop repeatable practices that enhance quality, speed, and consistency.

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Lead continuous improvement initiatives: Introduce new tools, processes, and working methods across the delivery organization, gather feedback, measure impact, and refine approaches based on results.

Requirements

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Relevant AI experience: Demonstrated experience working in the AI sector, particularly in startup environments, with responsibility for clients, teams, or projects at scale.

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Complex project management: Proven ability to manage complex projects from discovery and decomposition through scope planning, implementation, and adoption.

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Client-facing leadership: Significant experience managing client relationships and complex engagements. A consulting background at Engagement Manager, Associate Partner, or a comparable level is particularly relevant.

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AI and GenAI knowledge: Strong understanding of artificial intelligence and generative AI technologies, market trends, and practical applications.

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Technical foundation: Basic knowledge of statistics, machine learning, data science, and data generation, with the ability to collaborate effectively with technical specialists.

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Educational background: A bachelor's or master's degree in a STEM discipline, such as computer science, mathematics, or physics.

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Leadership and coordination: Ability to lead distributed, multidisciplinary teams, align stakeholders around shared objectives, and maintain accountability across complex delivery environments.

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Client communication: Excellent communication and relationship-management skills, including the ability to explain technical concepts, manage expectations, and navigate challenging conversations.

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Operational and commercial judgment: Strong organizational skills and the ability to balance quality, deadlines, resources, and financial performance.

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Problem-solving and adaptability: A proactive approach to resolving issues, managing ambiguity, and adapting plans as client needs and project requirements evolve.

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Continuous improvement mindset: Motivation to refine delivery processes, introduce effective working methods, and use data and feedback to improve performance.

Benefits

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Competitive compensation: A competitive compensation package; the specific salary range is not provided in the job description.

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Flexible remote work: A fully remote working arrangement with a flexible schedule.

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International environment: Opportunity to collaborate with a globally distributed team of AI specialists and professionals across multiple disciplines.

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Leading-edge technology: Exposure to advanced AI and generative AI projects that contribute to the development and evaluation of next-generation models.

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High-profile client projects: Opportunity to work with leading organizations in the AI industry, including major technology companies, established enterprises, and innovative AI startups.

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Professional growth: Opportunities to deepen expertise in AI delivery, client management, cross-functional leadership, and operational strategy.

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Meaningful impact: The chance to help shape AI innovation by ensuring complex data projects are delivered efficiently, reliably, and to high quality standards.

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Additional benefits: Healthcare coverage, paid leave, pension arrangements, equity, and other location-specific benefits are not specified in the provided job description and should be confirmed with the hiring team. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1