Senior Data Analyst – SFT & Data Labeling
TextRLHF
The main responsibility was handling Supervised Fine-Tuning (SFT) tasks to improve model performance on various data analysis queries. This involved creating, organizing, and validating training examples to align outputs with target responses for better model accuracy. Reporting and error analysis were also key parts of the process to ensure continuous model quality improvement.
• Curated datasets for SFT tasks.
• Improved training data structure and relevance.
• Conducted error reporting and feedback cycles.
• Supported model evaluation through labeled data.
The main responsibility was handling Supervised Fine-Tuning (SFT) tasks to improve model performance on various data analysis queries. This involved creating, organizing, and validating training examples to align outputs with target responses for better model accuracy. Reporting and error analysis were also key parts of the process to ensure continuous model quality improvement. • Curated datasets for SFT tasks. • Improved training data structure and relevance. • Conducted error reporting and feedback cycles. • Supported model evaluation through labeled data.
2024 - 2025