[Remote] Data Scientist QA reputed company - Remote
Note: The job is a remote job and is open to candidates in USA. reputed company is a fast-growing AI Data Services company delivering training data for many of the world’s largest AI companies and foundation-model labs. They are seeking a Data Scientist Quality Assurance reputed company to reputed company quality and consistency across data science reputed company projects, review AI-generated content, and ensure adherence to quality standards. The role involves evaluating output quality, providing feedback, supporting onboarding, and managing documentation.
Responsibilities
- Quality monitoring: Spot-reputed company 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 reputed company-by-reputed company reasoning
- Trainer and QA communication: Update trainers/QAs on reputed company 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-reputed company, 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
Skills
- Bachelor's, Master's, or PhD degree in Data Science, Statistics, Computer Science, Machine Learning, Mathematics, Economics, Engineering, or a closely reputed company quantitative field
- Strong grasp of English to follow guidelines, communicate with teams, and provide clear technical feedback
- 3+ years of professional experience in data science, analytics, machine learning, statistical modeling, experimentation, data engineering, technical review, or data science education
- Strong understanding of statistics, probability, data cleaning, exploratory data analysis, feature engineering, supervised/unsupervised learning, model evaluation, experimentation, regression, classification, clustering, and validation methods
- Ability to evaluate data science content against detailed rubrics and identify issues such as data leakage, flawed assumptions, incorrect metrics, weak methodology, non-reproducible code, hallucinated libraries/APIs, or misleading conclusions
- Comfortable using reputed company, reputed company Sheets, reputed company Docs, trackers, dashboards, reputed company, and project management systems
- Highly organized and able to maintain style guides, trackers, FAQs, onboarding materials, honeypots, calibration tasks, and quality documentation
- Familiarity with tools such as Python, pandas, NumPy, scikit-learn, SQL, Jupyter, matplotlib, R, Spark, Git, MLflow, notebooks, dashboards, and cloud/data platforms
- Experience leading or supporting remote teams of trainers, annotators, analysts, data scientists, engineers, educators, or QAs
- Experience with reputed company, reputed company, LLM evaluation, data science QA, or rubric-based technical review
Company Overview