Data Scientist Team Lead

SME Careers is a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. In this role, you will oversee quality assurance for data science AI training projects, ensuring content accuracy and adherence to project guidelines.

Responsibilities:

• Quality monitoring: Spot-check data science items, identify quality issues, provide feedback through DMs, and escalate recurring or critical issues
• Technical review: Evaluate AI-generated data science explanations, Python/R/SQL snippets, modeling workflows, statistical interpretations, dashboards, experiment designs, and step-by-step reasoning
• Trainer and QA communication: Update trainers/QAs on Discord about guideline changes, workflow updates, and data-science-specific quality expectations
• Question handling: Respond to questions around statistical assumptions, metrics, model selection, data leakage, validation, coding choices, reproducibility, and rubric interpretation
• Trainer/QA activation management: DM inactive contributors, encourage activation, track follow-ups, and flag availability issues
• Documentation: Create and maintain data science style guides, trackers, FAQs, examples, honeypots, calibration tasks, and onboarding materials
• Onboarding and training: Schedule and run onboarding/training calls with contributors to explain project expectations, workflows, rubrics, and data science review standards
• Risk review: Flag misleading, overconfident, statistically invalid, or non-reproducible data science outputs
• Process improvement: Identify recurring quality gaps and help build scalable QA processes