LLM Data Scientist: Labeling Strategy & Data Readiness

Eclipse Laboratories Inc.; United States; Remote; USD 120,000 - 190,000; Full time

Job summary

Eclipse Laboratories is seeking a Data Scientist to establish how our data is labeled, processed, and prepared for consumption by next-generation LLMs. Your work will transform raw data into AI-ready datasets.

You will define labeling strategies, automate data annotation workflows, and collaborate with engineering to build scalable data processing pipelines. Strong Python skills and experience with data-quality metrics are essential.

Qualifications

• Proven experience as Data Scientist or ML Engineer focused on data quality and prep.
• Strong knowledge of data labeling methodologies and annotation workflows.
• Experience preparing datasets for training/fine-tuning LLMs (tokenization, embeddings, NER).
• Proficient in Python and data-science libraries (Pandas, NumPy, scikit-learn, spaCy, HF).
• Experience using APIs/SDKs to automate data annotation and active learning.
• Excellent communication and ability to document complex topics clearly.

Responsibilities

• Develop data labeling strategies with scalable guidelines and quality metrics.
• Prototype data formats and preprocessing for LLM fine-tuning.
• Establish automated data quality analyses and metrics.
• Collaborate with engineering to guide data pipelines and infra.

Skills

Data quality

Data labeling

LLM data preparation

Python

APIs/SDKs

Documentation

Tools

Pandas

NumPy

Scikit-learn

spaCy

Hugging Face

Job description

Eclipse Laboratories is seeking a Data Scientist to establish how our data is labeled, processed, and prepared for consumption by next-generation LLMs. Your work will transform raw data into AI-ready datasets.

You will define labeling strategies, automate data annotation workflows, and collaborate with engineering to build scalable data processing pipelines. Strong Python skills and experience with data-quality metrics are essential.