Senior Data Scientist

Index Analytics LLC

Senior Data Scientist supporting government clients with AI solutions and machine learning techniques. Leading technical efforts and mentoring junior data scientists in a collaborative environment.

Posted 7/9/2026full-timeRemote • Maryland • 🇺🇸 United StatesSenior💰 $155,800 - $194,250 per yearWebsite

Tech Stack

Tools & technologies

AirflowAmazon RedshiftAWSCloudDynamoDBJenkinsNumpyPandasPythonPyTorchScikit-LearnTensorflow

About the role

Key responsibilities & impact

Serve as a technical lead on AI and machine learning initiatives, providing guidance on solution architecture, model selection, implementation approaches, and technical best practices.
Mentor and support junior and mid-level data scientists through code reviews, knowledge sharing, technical coaching, and collaborative problem solving.
Establish and promote best practices for MLOps, model evaluation, model monitoring, reproducibility, and responsible AI development
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.
Evaluate emerging AI technologies, frameworks, and techniques and recommend their appropriate application to government healthcare use cases.
Perform data mining and exploratory data analysis (EDA) using state-of-the-art techniques across structured and unstructured datasets.
Contribute to technical leadership across multiple AI initiatives while remaining an active hands-on developer and model builder.
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.

Requirements

What you’ll need

U.S. citizen or otherwise authorized to work in the United States and able to demonstrate physical residency in the U.S. for at least three (3) of the past five (5) years.
Must be able to obtain a U.S. Federal government client badge and pass a Public Trust clearance.
Master’s degree in Computer Science, Data Science, or a related field required; PhD preferred.
Five (5) or more years of experience as a Data Scientist or in a similar role.
Strong experience in machine learning and statistical modeling, including supervised and unsupervised learning techniques, deep learning, and a solid foundation in probability, hypothesis testing, and regression.
Demonstrated experience serving as a technical lead, senior individual contributor, or subject matter expert on machine learning or AI projects.
Proven track record of deploying, maintaining, and monitoring machine learning and AI solutions in production environments.
Strong understanding of MLOps practices, including model versioning, CI/CD workflows, monitoring, testing, and operational support.
Proven expertise in NLP and text analytics, including transformer-based architecture (e.g., BERT and related models), embeddings, vector databases, and semantic search systems.
Hands-on experience building LLM-powered applications, including prompt engineering, RAG architecture, and ideally agentic workflows or LLM orchestration frameworks, preferably within AWS environments (e.g., Bedrock).
Advanced programming skills in Python (preferred) and/or R, with practical experience using ML and data libraries such as pandas, NumPy, scikit-learn, PyTorch, and TensorFlow.
Strong experience with AWS cloud and MLOps tooling, including SageMaker, S3, Glue, Airflow, and data stores such as Redshift and DynamoDB, along with version control (GitHub) and CI/CD pipelines (e.g., Jenkins).
Experience with backend systems and data integration, including data modeling and supporting APIs for web-based and production applications.
Strong written and verbal communication skills, with the ability to explain complex models and insights clearly.
Experience supporting CMS or other federal healthcare agencies is a plus.

Benefits

Comp & perks

health and retirement benefits
discretionary bonuses
reimbursement for professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Statistical ModelingDeep LearningPredictive AnalyticsData MiningExploratory Data AnalysisPrompt EngineeringRAG ArchitectureModel Evaluation MetricsProgramming in PythonData Visualization

Soft Skills

MentoringCollaborationCommunication

Certifications

Master’s Degree in Computer ScienceMaster’s Degree in Data SciencePhD Preferred