Data Scientist

The ideal candidate is a Data Scientist with 1-4 years of experience and a Computer Science or Statistics Degree. This individual will:

~Oversee day to day ops of AWS, Microsoft 365, multi auth work with 'duo' (a tool)

~Write models to find key document sets (often times in millions of records of text data)

~Need strong STATS capabilities (core math capabilities)

• Key Responsibilities
  :
  Develop Python-based pipelines for extracting and processing text and metadata from documents, including both native text and image-based content.
• Design and implement AI workflows using open-source and commercial large language models for classification, summarization, extraction, and analysis tasks.
• Build and maintain vector indexes and retrieval-augmented generation (RAG) workflows to support document-heavy legal use cases.
• Implement prompt templates and prompt design patterns to support consistency and reuse across client matters.
• Deploy, operate, and support AI workflows in AWS environments, including use of Sage Maker for model training, experimentation, and inference.
• Apply traditional machine learning techniques (e.g., logistic regression, random forest, decision trees) where appropriate alongside LLM-based approaches.
• Support statistical validation efforts, including sampling, metric calculation, and basic error analysis to evaluate model performance.
• Work with SQL and MySQL to support data analysis, validation, and pipeline integration.
• Produce clear, detailed documentation describing data sources, model behavior, validation results, and assumptions to support transparency and review.
• Required Qualifications
  :
  Experience in applied machine learning, NLP, and data engineering.
• Strong Python proficiency with experience building data processing or ML pipelines.
• Experience extracting and processing text from structured and unstructured documents, including images (e.g., OCR workflows).
• Hands-on experience working with open-source and/or commercial large language models.
• Experience deploying or supporting ML workflows in AWS, including Sage Maker.
• General competency with SQL and MySQL for data storage, querying and analysis.
• Foundational understanding of statistical validation concepts, including sampling and performance metrics.
• Experience with prompt templating and structured prompt design.
• Experience building or working with vector indexes and RAG frameworks.
• Working knowledge of classical machine learning models, including logistic regression.
• Strong attention to detail and a disciplined approach to documentation.