Senior Data Scientist

This is a fully remote position, open to applicants in Maryland.

📋 Description

• Act as a technical leader in AI and machine learning projects, offering expertise on solution architecture, model selection, implementation strategies, and technical best practices.

• Guide and nurture junior and mid-level data scientists through code assessments, knowledge transfer, technical mentorship, and collaborative problem-solving.

• Develop and advocate for best practices in MLOps, model assessment, model monitoring, reproducibility, and responsible AI development.

• Construct and implement comprehensive ML pipelines on AWS (e.g., SageMaker, S3, Glue) for efficient training, evaluation, and inference.

• Create and execute advanced NLP solutions, such as text classification, entity recognition, topic modeling, and semantic search utilizing models like BERT and transformer-based architectures.

• Design, establish, and operationalize RAG (Retrieval-Augmented Generation) systems, encompassing document ingestion, embedding pipelines, vector search, and LLM orchestration.

• Develop applications powered by LLMs, focusing on prompt engineering, evaluation frameworks, and optimization techniques for accuracy, consistency, and cost-effectiveness.

• Contribute to the design of agentic AI systems, including workflows for multi-step reasoning, tool usage, and orchestration of LLM-driven agents for complex tasks.

• Apply predictive analytics and statistical modeling to identify patterns, trends, and insights from healthcare data.

• Assess emerging AI technologies, frameworks, and methodologies, and suggest their suitable application for government healthcare use cases.

• Conduct data mining and exploratory data analysis (EDA) utilizing cutting-edge techniques across both structured and unstructured datasets.

• Provide technical leadership across various AI initiatives while remaining actively engaged as a developer and model builder.

• Create data visualizations, dashboards, and analytical tools to effectively convey findings to both technical and non-technical stakeholders.

• Assess model performance using relevant metrics (e.g., accuracy, AUC, precision/recall) and communicate results in a clear, actionable format.

• Collaborate in an Agile setting with cross-functional teams, including engineers, analysts, and stakeholders.

• Propose data-driven solutions and AI strategies that align with CMS business objectives and healthcare policy goals.

⛳️ Requirements

• U.S. citizen or otherwise authorized to work in the United States, with at least three (3) of the past five (5) years of physical residency in the U.S.

• Ability to obtain a U.S. Federal government client badge and pass a Public Trust clearance.

• A Master’s degree in Computer Science, Data Science, or a related field is required; a PhD is preferred.

• Minimum of five (5) years of experience as a Data Scientist or in a related role.

• Strong background in machine learning and statistical modeling, covering both supervised and unsupervised learning techniques, deep learning, and a solid understanding of probability, hypothesis testing, and regression.

• Proven experience acting as a technical lead, senior individual contributor, or subject matter expert in machine learning or AI projects.

• Demonstrated success in deploying, maintaining, and monitoring machine learning and AI solutions in production settings.

• In-depth knowledge of MLOps practices, including model versioning, CI/CD workflows, monitoring, testing, and operational support.

• Expertise in NLP and text analytics, including transformer-based architectures (e.g., BERT and related models), embeddings, vector databases, and semantic search systems.

• Practical experience in building LLM-powered applications, such as prompt engineering, RAG architecture, and ideally agentic workflows or LLM orchestration frameworks, preferably within AWS environments (e.g., Bedrock).

• Advanced programming abilities in Python (preferred) and/or R, with hands-on experience using ML and data libraries such as pandas, NumPy, scikit-learn, PyTorch, and TensorFlow.

• Extensive experience with AWS cloud and MLOps tools, including SageMaker, S3, Glue, Airflow, and data stores like Redshift and DynamoDB, along with version control (GitHub) and CI/CD pipelines (e.g., Jenkins).

• Familiarity with backend systems and data integration, including data modeling and supporting APIs for web-based and production applications.

• Excellent written and verbal communication skills, capable of clearly explaining complex models and insights.

• Experience working with CMS or other federal healthcare agencies is a plus.

🏝️ Benefits

• Health and retirement benefits

• Discretionary bonuses

• Reimbursement for professional development opportunities