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Data Scientist - Statistics/ML - Remote

Molina HealthcareUnited States🌍 Remote
Full-timeMid Level
👁️ 0 views📝 0 applicationsPosted 8/29/2026Expires 10/28/2026
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Job Description

Job Summary Perform data and error analysis to improve models, and clean and validate data for uniformity and accuracy. Execute data science and statistical analytical experiments methodically to help solve various problems and make a true impact across various healthcare domains.

Developing and deploying advanced machine learning models and AI solutions that enhance our products and services. Leverage their expertise in data science, machine learning, and AI technologies to derive insights from large datasets and create predictive models that drive business decisions.

Job Duties Data Analysis and Interpretation: Extract meaningful insights from complex datasets, identify patterns, and interpret data to inform strategic decision-making.

• Machine Learning Model Development: Design, develop, and train machine learning models using a variety of algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning.

• Agentic Workflows Implementation: Develop and implement agentic workflows that utilize AI agents for autonomous task execution, enhancing operational efficiency and decision-making capabilities.

• RAG Pattern Utilization: Employ retrieval-augmented generation patterns to improve the performance of language models, ensuring they can access and utilize external knowledge effectively to enhance their outputs.

• Model Fine-Tuning: Fine-tune pre-trained models to adapt them to specific tasks or datasets, ensuring optimal performance and relevance in various applications.

• Data Cleaning and Preprocessing: Prepare data for analysis by performing data cleaning, handling missing values, and removing outliers to ensure high-quality inputs for modeling.

• AI Model Deployment and Monitoring: Deploy AI models into production environments, monitor their performance, and adjust as necessary to maintain accuracy and effectiveness.

• Collaboration: Work closely with cross-functional teams, including software e

Required Skills

Cross-functional CollaborationData AnalysisData ScienceDeep LearningMachine LearningStatistics

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