Lead Data Intelligence Project Manager

About Dyson

Dyson is fueled by continuous innovation in engineering, artificial intelligence, and robotics. Our Data Intelligence team is central to this mission, shaping the future through strategic data initiatives that empower intelligent products. Within this team, creativity, accuracy, and bold ideas converge to develop data infrastructures that enable the upcoming generation of connected devices.

Joining us means collaborating with talented professionals from Dyson's global engineering division and external technology partners in an environment that fosters exploration, discovery, delivery, and meaningful impact.

Role Overview

As the Lead Data Intelligence Project Manager, you will oversee resource allocation ensuring projects launch smoothly. You'll coordinate data-related operations crucial to product advancement across Dyson's worldwide teams.

• Serve as the main point of contact between external project teams and internal technical groups such as Data Curation and MLOps, managing the entire data logistics process—from initial storage preparation to delivering precise training datasets.
• Lead the strategy for managing the labeling workforce by balancing the efforts of internal contractors and third-party providers to avoid capacity shortages.
• Supervise the setup and maintenance of data storage solutions ensuring security, usability, and regulatory compliance.
• Ensure comprehensive documentation and well-defined workflows that promote transparency and repeatability in projects.
• Facilitate effective communication between data teams, contractors, and engineering partners.

Candidate Profile

• 8 or more years of experience in Project or Program Management, with at least two years specifically in AI/ML Data Operations or Data Management, demonstrating successful delivery of complex projects in dynamic environments.
• Proven expertise in managing third-party vendors or service providers, including contract negotiations, quality control, issue resolution, and relationship upkeep.
• Strong comprehension of the Machine Learning lifecycle including data collection, cleansing, labeling, training, and deployment.
• Familiarity with labeling platforms like Labelbox, CVAT, Label Studio, and project management software such as Jira, Asana, or Airtable.
• Basic knowledge of data storage systems like S3, SQL databases, Snowflake, along with understanding of data privacy regulations such as GDPR and CCPA.
• Exceptional communication skills capable of translating technical MLOps constraints for business stakeholders and vice versa.
• Deep understanding of modern data storage architectures (cloud, on-premises, hybrid), data security principles, privacy controls, access management, and compliance standards.
• Capability to convert complex technical requirements into actionable steps understandable by both technical and non-technical teams, with strong influencing and consensus-building skills.
• Experienced in coordinating cross-functional collaborations among data scientists, engineers, product managers, and external parties to ensure seamless project handoffs and alignment.
• Proficient in project management methodologies including Agile, Scrum, and Waterfall, noted for driving continuous process improvements, thorough documentation, and reproducible workflows.
• Highly organized, diligent in identifying and resolving blockers proactively before impacting timelines.
• Self-motivated, responsible, and adept at managing competing priorities while maintaining focus on end objectives and balancing urgency with quality.
• Holds a relevant Bachelor's degree such as in Computer Science, Data Engineering, Engineering, or Information Technology. Advanced degrees or certifications like PMP or Prince2 are advantageous.

Diversity & Equal Opportunity

Dyson is an equal opportunity employer valuing diversity in thought and background. Employment decisions are made without consideration to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity, age, disability, veteran status, or any other diversity dimension.