Data Scientist Supply Chain Operations

• Data Preprocessing: Clean, transform, and prepare data for development and analysis within a data warehouse composed of supply chain information. Ensure data quality, integrity, and consistency.
• Development: Use Python and SQL to build and maintain automation processes, such as RPA and email bots, utilizing tools like relay servers and workflow schedulers for internal use by a wide range of supply chain professionals.
• Data Integration: Design, code, and maintain data pipelines that bring together disparate healthcare data sources, including Electronic Health Records (EHR) systems, Enterprise Resource Planning (ERP) systems, and external data feeds from SFTP servers and APIs with a heavy emphasis on cloud-based solutions. Ensure that data is collected, stored, and processed efficiently for analysis.
• Data Analysis: Analyze large and complex healthcare datasets to identify patterns, trends, and anomalies. Use statistical techniques to draw meaningful conclusions from data.
• Error Handling: Provide advanced technical support on application performance issues, determine root causes, and implement system fixes and improvements.
• Data Architecture: Build data storage, data warehousing, cloud integration, and data modeling strategies to support data analytic initiatives effectively.
• Data Visualization: Create compelling data visualizations and dashboards to communicate findings and insights to non-technical stakeholders.
• Machine Learning: Develop and implement predictive models, classification algorithms, and other machine learning techniques to solve supply chain oriented problems, such as automating supply chain processes and resource allocation optimization.

• Coding Standards: Write code that meets internal standards for style, maintainability, and best practices for a high-scale database environment. Maintain and advocate for these standards through code review.
• Agile: Work in an agile environment across developers, analysts, project managers, leaders, and stakeholders utilizing Azure DevOps or a similar project management system.
• Pair Programming: Actively participate in pair programming sessions with fellow data scientists involving a driver, a person who writes the code, and a navigator, a person who reviews each line of code.
• Dynamic Environment: Function independently on multiple programming projects with competing priorities and adapt quickly to new ideas and disparate data environments like Oracle and Redshift.
• Data Security and Compliance: Ensure that all data handling and analysis comply with relevant healthcare regulations and protect patient privacy.
• Continuous Improvement/Continuous Development (CI/CD): Adopts a continuous improvement culture seeking to make good processes better and to elevate those that need work.
• Research and Development: Stay up-to-date with the latest advancements in healthcare analytics and data science, and actively contribute to the development of innovative solutions.

• Collaboration: Collaborate with cross-functional teams, such as, data engineers, SMEs, and IT professionals, to understand data requirements, business objectives, and supply chain workflows.
• Stakeholder Interaction: Work collaboratively with various stakeholders of differing backgrounds. Being able to explain complex technical concepts in simple terms.
• Presentation: Story-telling with data in a coherent manner to communicate the significance of analysis and findings.
• Understanding Business Objectives: Comprehend business requirements behind analysis, which involves actively engaging with stakeholders to grasp their needs, challenges, and objectives.
• Reporting: Collaborate to develop and refine reports and ad-hoc queries for presentations that convey key findings and their potential impact on healthcare operations so stakeholders can make informed decisions.

Remote eligible.

The job summary and responsibilities listed above are designed to indicate the general nature of the work performed within this job. They are not designed to contain or be interpreted as a comprehensive inventory of all job responsibilities required of employees assigned to this job. Employees may be required to perform other duties as assigned.