Data Scientist (AI Data & LLM Specialist)

Qualifications

• Proven experience as a Data Scientist or Machine Learning Engineer with a focus on data quality and preparation.
• Strong understanding of data labeling methodologies and hands-on experience with data annotation platforms and workflows.
• Demonstrated experience preparing datasets for training and fine-tuning Large Language Models (LLMs), including knowledge of techniques like tokenization, embeddings, and NER.
• Proficiency in Python and common data science libraries (e.g., Pandas, NumPy, Scikit-learn, spaCy, Hugging Face).
• Experience using APIs/SDKs to automate data annotation and active learning loops.
• Excellent communication skills, with an ability to create clear documentation for technical and non-technical audiences.

Responsibilities

• Develop Data Labeling Strategies: Design and document a formal data annotation strategy, including clear, scalable, and efficient guidelines for labeling our data. Define and enforce quality metrics, including inter-annotator agreement.
• Optimize for LLM Consumption: Research, define, and prototype the optimal data formats, structures, and pre-processing steps required for fine-tuning and training LLMs on our datasets.
• Data Quality Analysis: Establish automated processes and metrics to analyze the quality of both raw and labeled data, providing feedback to improve our data collection and labeling workflows.
• Collaborate with Engineering: Work closely with the engineering team to guide the implementation of data processing pipelines and ensure the data infrastructure meets the needs of ML applications.