Dataset Operations Manager

Data Science UA is a service company with deep expertise in AI and Data Science. Our story started in 2016 with the first Data Science UA Conference in Kyiv, and since then, we’ve built one of the largest AI communities in Europe.

About the role and client:
We are looking for Dataset Operations Manager to the clients team - a leading Ukrainian manufacturer of autonomy technologies for drones. The role mission is to ensure the full data lifecycle: from strategic project planning to quality assurance and validation of final deliverables.

Responsibilities:
- Planning & Prioritization: Plan and prioritize dataset projects in alignment with the ML team's roadmap and product goals.
- Synthetic Data Generation Ownership: Own the synthetic data generation direction — coordinate pipeline development, prioritize scenarios, and control the quality of generated data.
- Manual Data Annotation Team Ownership: Lead the manual data annotation team — handle hiring, onboarding, performance reviews, tool training, and quality control.
- Team Coordination: Coordinate dataset engineers and the annotation team — assign tasks, track progress, and balance workloads.
- Requirements Alignment: Align dataset requirements with ML engineers — translate ML model training needs into dataset specifications and definition of done (criteria of readiness).
- Capacity & Resource Management: Forecast capacities, reallocate workloads, and resolve blockers.
- Project-Level Quality Tracking: Monitor project-level metrics of dataset deliverables and identify systemic issues.
- Vendor Management: Manage external annotation partners — handle vendor evaluation, contracting, and quality control.
- Processes & Standards Maintenance: Maintain workflows, documentation, and SLAs for working with datasets.
- Reporting: Report on dataset projects to leadership and the ML team — sharing status, progress, risks, and blockers.
- Continuous Improvement: Continuously optimize processes to improve annotation throughput, cycle times, and reduce error rates.
- Platform Support: Support the dataset catalog platform from a process and organizational perspective.

Requirements:
- 2+ years of experience in a similar role.
- People Management: Proven experience in direct management — hiring, developing, and building workflows for manual annotators.
- Data & ML Literacy: Solid understanding of the ML lifecycle and experience working with data (knowledge of data types, structures, and processing methods).
- Synthetic Data: Understanding of synthetic data generation principles and automated data collection approaches.
- Analytical Skills: Ability to forecast capacity, identify process bottlenecks, and propose optimization solutions.

Nice to have:
- Knowledge of the MilTech / DefTech market.