About the role
As the Lead Data Intelligence Project Manager, you will ensure that every project has the resources it needs to take off, orchestrating data operations that power product development across the global teams. Key responsibilities include:
- Acting as the primary liaison between external project teams and internal technical departments (Data Curation and MLOps), owning the "data logistics" for the entire project lifecycle—from initial storage setup to final delivery of high-quality training sets.
- Serving as the strategic lead for the labelling workforce, managing the balance between in-house contractors and 3rd party service providers to ensure capacity bottlenecks are avoided.
- Overseeing data storage setup and maintenance to guarantee security, accessibility, and compliance.
- Maintaining rigorous documentation and workflows that ensure project transparency and repeatability.
- Supporting cross-functional communication between data teams, contractors, and engineering partners.
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About you
- 8+ years in Project or Program Management, with at least 2 years specifically in AI/ML Data Operations or Data Management. You have a track record of delivering complex projects on time and within scope—often in fast-changing settings.
- Demonstrated success in managing 3rd party vendors or service providers, including contract negotiation, quality assurance, issue resolution, and ongoing relationship management.
- Strong understanding of the Machine Learning Lifecycle: knowledge of how data flows from collection → cleaning → labeling → training → deployment.
- Experience with tooling: familiarity with labeling platforms (Labelbox, CVAT, Label Studio) and project management tools (Jira, Asana, or Airtable).
- Basic data literacy: understanding of data storage architectures (S3, SQL, Snowflake) and data privacy regulations (GDPR, CCPA).
- Exceptional communication skills: capable of explaining technical MLOps constraints to business stakeholders and vice versa.
- Solid understanding of modern data storage solutions (cloud, on-premises, hybrid), including principles of data security, privacy, access control, and regulatory compliance.
- Ability to translate complex technical requirements into clear actions for both technical and non-technical audiences, adept at influencing and building consensus.
- Confident in interfacing with cross-functional teams—coordinating with data scientists, engineers, product managers, and external stakeholders to ensure smooth handovers and alignment.
- Well-versed in project management tools and methodologies (e.g., Agile, Scrum, or Waterfall) with a focus on driving continuous improvement, clear documentation, and repeatable processes.
- Highly organized and thorough, relentless in troubleshooting issues and removing blockers before they impact delivery.
- Proactive and accountable, comfortable juggling competing priorities while keeping end goals in focus and balancing urgency with quality.
- A Bachelor’s degree in a relevant discipline (e.g., Computer Science, Data Engineering, Engineering, or Information Technology); a higher degree or PMP/Prince2 certification is a plus.
The company is an equal opportunity employer. We value diversity and welcome applications from individuals of all backgrounds. Employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status, or any other dimension of diversity.
