Senior Data Scientist – ML Classification & Content Safety

📋 Description

• Define evaluation methodology for content classification; require model cards before ship.
• Lead multiclass refactor: convert binary classifiers to multi-label, multi-class categories (Adult Content, Violence, Self-Harm, Social Media).
• Build labeled evaluation datasets; address imbalance; document dataset curation decisions.
• Connect offline evaluation to production monitoring; surface classification drift and error patterns early.
• Investigate misclassifications; produce root-cause analyses and corrective actions.
• Build training data pipelines: ingestion, cleaning, labeling, and versioning at scale.

🎯 Requirements

• Multi-label/multi-class ML with robust evaluation; handle class imbalance.
• Python ML stack: scikit-learn, PyTorch or TF, pandas, numpy.
• NLP features for web content: URL tokenization, domain analysis, TF-IDF or embeddings.
• Rigorous evaluation: precision/recall tradeoffs, confusion matrices, A/B testing.
• Data engineering for ML: training pipelines, data versioning, labeling workflows.
• Technical communication with engineers and leadership; drive stakeholder influence.

🎁 Benefits

• Comprehensive Health Insurance (employee, parents, spouse, children)
• Accidental & Term Life Insurance
• Learning & Development reimbursement
• Paid Time Off
• Public Holidays (10+ per year)
• Retirement Benefits (EPF & gratuity)