Data Science/Machine Learning Engineer (Remote, Continental United States)

5+ years of overall professional experience in data science, analytics, or a related field. 2–3 years of hands-on experience focused on Large Language Models (LLMs) and related techniques. Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field. Coding knowledge and experience with Python. Proven ability to use statistical computer languages (Python, R, SQL, etc.) for data manipulation, analysis, and model development. Experience with Hugging Face Transformers, LangChain, Llama Index, and/or large-scale training frameworks. Familiarity with LLM evaluation, interpretability, and best practices. Knowledge of ML and data mining techniques. Familiarity with AWS services (Athena, S3, Glue, SageMaker, Bedrock) for scalable model development. NLP Techniques (NER, Information Extraction, Text Categorization, Document Parsing). Ability to obtain a Public Trust Clearance.

Identify data-driven opportunities aligning with business goals. Mine and analyze complex datasets using statistical and ML approaches. Assess new data sources and data gathering techniques. Perform data processing using LLM models. Assess new data sources and data gathering techniques to enhance data strategy with ML/AI methods. Develop presentations and demos for analytical solutions. Use advanced statistical and ML approaches for business improvements. Establish processes to track model performance and iterate on models.