Machine Learning (Data) Specialist - MEDCHART

The Machine Learning (Data) Scientist - Senior will lead the Data Admin & Analytics Department, overseeing the development and deployment of machine learning models and managing the data lifecycle within a secure government environment handling sensitive medical information. This role involves ensuring data quality, compliance with HIPAA and FISMA regulations, and the integration of key tools such as Microsoft Azure Machine Learning, Power BI, and other relevant Microsoft products to enhance data analytics capabilities.

Position Responsibilities:

• Lead and supervise the Data Admin & Analytics Department, including two Advanced Database Analysts, providing guidance, support, and performance evaluations.
• Oversee data collection, integration, cleaning, and preparation processes, ensuring data quality, consistency, and compliance with regulations.
• Design, develop, and deploy machine learning models using tools like Microsoft Azure Machine Learning, Python, and R to address complex business challenges.
• Develop interactive dashboards and visualizations using Microsoft Power BI to present data insights and model predictions to stakeholders.
• Perform advanced data analysis to describe trends, predict outcomes, and identify causal relationships within the data.
• Collaborate with cross-functional teams to align data initiatives with organizational goals and security requirements.
• Communicate complex technical concepts and data-driven insights to non-technical stakeholders through presentations and written reports.
• Stay updated with the latest advancements in machine learning and data science methodologies to continuously enhance capabilities.
• Ensure all data science activities comply with relevant standards and maintain detailed documentation for auditing and replication purposes.
• Implement data governance frameworks to ensure data integrity, security, and proper documentation throughout the data lifecycle.
• Develop and manage data pipelines for efficient data processing, model training, and deployment.
• Conduct regular audits and assessments of data processes to identify and rectify potential issues.
• Drive innovation by exploring and adopting new data science techniques and tools that can enhance organizational growth and operational efficiency.
• Lead cross-departmental initiatives that leverage data science to address broader organizational challenges and drive innovation.
• Provide training and support to end-users and other departments on data tools, dashboards, and machine learning insights, fostering a data-driven culture within the organization.