Senior Data Scientist

Job Description

Job Details:

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Job Title: Senior Data Scientist II

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Duration: Long-Term Contract

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Location: Raleigh, NC || Onsite / Remote (EST Only)

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Note: Preference will be given to candidates with Mandarin language proficiency.

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Job Description:

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Key Responsibilities

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• Develop and improve LLM-based workflows for information extraction, classification, legal summarization, and content generation.

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• Design and evaluate prompts, retrieval-augmented generation (RAG), and multi-step agent workflows.

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• Build reliable data-preparation pipelines, including parsing, transformation, validation, caching, and recovery from interrupted processing.

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• Create representative evaluation datasets and conduct controlled experiments, error analysis, and regression testing.

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• Work with subject matter experts to assess factual accuracy, completeness, source support, and consistency, and translate feedback into generalizable improvements.

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• Diagnose problems across data, retrieval, model behavior, and application logic.

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• Balance output quality, latency, and cost when comparing technical approaches.

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• Maintain tested, version-controlled code and clear documentation to support reproducibility and team handoffs.

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Required Qualifications

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• Bachelor’s degree or higher in computer science, Data Science, Statistics, Mathematics, or a related quantitative field, or equivalent practical experience.

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• At least 3 years of relevant experience in data science, machine learning, or NLP, including hands-on experience developing LLM-based applications.

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• Strong Python programming skills and experience with SQL and structured or semi-structured data, such as JSON and XML.

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• Practical experience with prompt design, structured outputs, retrieval, and systematic LLM evaluation.

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• Understanding of statistical evaluation, train/validation/test separation, data leakage, and appropriate performance metrics.

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• Experience using Git, debugging existing code, and writing automated tests.

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• Ability to communicate findings clearly, incorporate feedback, and proactively raise delivery risks.

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Preferred Qualifications

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• Experience with traditional machine learning, including feature engineering, classification, tree-based models, and imbalanced datasets.

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• Familiarity with scikit-learn, PyTorch, or comparable frameworks.

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• Experience fine-tuning transformer models for classification, information extraction, or sequence labeling.

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• Familiarity with AWS, particularly S3 and EC2, and Linux or GPU-based training environments.

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• Experience with legal documents, editorial workflows, or other accuracy-sensitive domains.

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What are the top 3 must-have skills?

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• Applied LLM development: demonstrated experience building and evaluating workflows involving prompts, retrieval, and structured generation.

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• Python and data engineering: ability to independently build, debug, and maintain reliable data-processing and model-integration code.

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• Experimental design and evaluation: ability to compare baselines, analyze errors, validate improvements, and communicate actionable findings.

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