134 applicants

Company

Elder Research · 1 day ago

Senior Data Scientist - Cleared

United States

Full-time

Remote

Mid, Senior Level

4+ years exp

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AnalyticsConsulting

Growth Opportunities

No H1B

U.S. Citizen Only

Security Clearance Required

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Responsibilities

Developing improved risk adjustment methodologies using AI that are rigorously derived, thoroughly tested, and defensible, and have the potential to inspire confidence among stakeholders;

Devising AI algorithms that can assist CMS in understanding and addressing coding intensity and risk score growth to improve on CMS’ existing policies to account for coding intensity;

More accurately understanding the 'optimal' cost of care for a given beneficiary in the context of health equity and improving care access and quality for underserved beneficiaries;

Accounting for practical considerations by identifying and preventing or mitigating potential unintended consequences that could arise from AI-assisted risk adjustment and coding intensity adjustment.

Develop and train advanced machine learning models, with a focus on building recommendation systems and enhancing predictive accuracy.

Perform feature engineering to improve model performance and adapt to various data sources and structures.

Leverage expertise in Large Language Models (LLMs) and Natural Language Processing (NLP) to create intelligent, context-aware applications.

Apply machine learning and deep learning techniques, particularly with neural networks, for tasks such as time-series forecasting and complex data analysis.

Maintain a strong focus on ML development best practices, including data preparation, model evaluation, and continuous improvement.

Participate in meetings as appropriate to support the program goals.

Perform literature research on mutually identified areas of interest to support program goals.

Suggest potential statistical, machine learning, and AI analytical approaches, methodologies and techniques that might further progress against the anticipated outcomes described above. Including, but not limited to, the description, literature review, documentation, and communication of those potential approaches.

Research, review, and discuss and topics related to topics of interest to the program.

Provide suggestions on the application of statistical and machine learning algorithms to the analysis being performed such as the choice of statistical model and hyper parameters, predictive features, and definition of the target variable(s).

Provide feedback and guidance on the use of algorithms and formulas used in computer code for training machine learning and AI models or deriving statistics for output.

Review and provide feedback on analysis outputs performed by other members of the team. The analysis outputs might include statistical output, slides, or documentation of results and findings.

Perform data preparation tasks to apply transformations needed for statistical analysis, machine learning, and/or AI analytical approaches.

Create technical artifacts such as scripts or notebooks to perform potential statistical, machine learning, and AI analytical approaches.

Manage source code versioning with available tools such as Github.

Perform quality control (QC) checks on developed code and assist in QC initiatives on the project as appropriate.

Prepare materials such as presentation slides or reports for discussion on technical topics.

Assist in the development of the documents such as the Analysis Plan and Findings Report which could include drafting, editing, or reviewing sections of the document.

Qualification

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Data ScienceMachine LearningAI AlgorithmsNatural Language ProcessingDeep LearningFeature EngineeringLarge Language ModelsTime-Series ForecastingStatistical AnalysisPythonGithubHealthcare ExperienceClaims DataICD-10 DataRecommender ModelsXGBoostLSTMEmbedding Models