Data Scientist

Index Analytics, LLC, is a rapidly growing, Baltimore-based small business providing health-related consulting services to the federal government. At the center of our company culture is a commitment to instilling a dynamic and employee-friendly place to work. We place a priority on promoting a supportive and collegial team environment and enhancing staff experience through career development and educational opportunities.

Index Analytics is seeking a Data Scientist to support Government clients in the Baltimore and Washington D.C. Metro Area. This resource will create value from structured and unstructured data by applying domain knowledge, statistical analysis, and advanced machine learning techniques to solve complex healthcare challenges.

This role emphasizes end-to-end development of machine learning and AI systems, including traditional ML, deep learning, NLP, and modern LLM-based architectures such as Retrieval-Augmented Generation (RAG) and agentic AI systems.

Responsibilities

• Design, develop, and maintain machine learning and deep learning models, including both traditional (e.g., regression, tree-based models) and neural network-based approaches.
• Build and deploy end-to-end ML pipelines on AWS (e.g., SageMaker, S3, Glue) for scalable training, evaluation, and inference.
• Develop and implement advanced NLP solutions, including text classification, entity recognition, topic modeling, and semantic search using models such as BERT and transformer-based architectures.
• Design, build, and productionize RAG (Retrieval-Augmented Generation) systems, including document ingestion, embedding pipelines, vector search, and LLM orchestration.
• Develop LLM-powered applications, including prompt engineering, evaluation frameworks, and optimization techniques for accuracy, consistency, and cost.
• Contribute to agentic AI system design, including multi-step reasoning workflows, tool use, and orchestration of LLM-driven agents for complex tasks.
• Implement predictive analytics and statistical modeling to uncover patterns, trends, and insights from healthcare data.
• Perform data mining and exploratory data analysis (EDA) using state-of-the-art techniques across structured and unstructured datasets.
• Build data visualizations, dashboards, and analytical tools to communicate findings clearly to technical and non-technical stakeholders.
• Evaluate model performance using appropriate metrics (e.g., accuracy, AUC, precision/recall) and present results in a clear, actionable manner.
• Collaborate in an Agile environment with cross-functional teams including engineers, analysts, and stakeholders.
• Recommend data-driven solutions and AI strategies aligned with CMS business needs and healthcare policy objectives.