Data Scientist

Overview

The Data Scientist will play a crucial role in advancing the CDC Foundation's mission by leveraging data to inform strategic decisions and initiatives in a public health organization. This role is aligned to the Workforce Acceleration Initiative (WAI). WAI is a federally funded CDC Foundation program with the goal of helping the nation’s public health agencies by providing them with the technology and data experts they need to accelerate their information system improvements.

Working within the Michigan Department of Health and Human Services (MDHHS), the Data Scientist will provide detailed, tailored technical assistance and training to local and state public health teams in the use of advanced analytics, statistical techniques, and machine learning algorithms to derive insights that support public health efforts. Specifically, MDHHS is working with local public health and an academic partner to develop an enterprise data platform (EDP) proof of concept (POC) that will be rolled out across local public health and the state public health agency.

The incumbent in this role will provide the upskilling support to end-users that results in the competency needed for ongoing, sustained adoption of the platform. The incumbent will work with a data modernization senior advisory and project partners to develop and implement the technical assistance and training curriculum needed. The incumbent will also have the opportunity to work on data, analytics, and modeling efforts together with MDHHS and academic partners.

The Data Scientist will be hired by the CDC Foundation and assigned to the Michigan Department of Health and Human Services (MDHHS). This position is eligible for a fully remote work arrangement for U.S. based candidates.

• Develop, implement, and improve data analysis and visualization tools for use by project partner teams, to provide timely, relevant information that informs decisions impacting public health.
• Work with project partners to provide direct technical assistance and mentorship in the analysis of diverse datasets related to public health issues to identify trends, patterns, and correlations.
• Apply statistical methods and machine learning algorithms to extract actionable insights.
• Assist project partners in the development of predictive models to anticipate disease patterns, assess risk factors, and guide intervention approaches. This may include coordination with academic partner teams focused on disease modeling and analytics efforts.
• Support the ongoing optimization of algorithms for enhanced accuracy and performance.
• Support project partners in the creation of compelling visualizations and reports to communicate findings to partners and decision-makers.
• Present data-driven insights in a clear and understandable manner to facilitate informed decision-making.
• Collaborate with the public health organization and its partners to understand their data needs and objectives.
• Provide data-driven support and guidance to inform public health policies and initiatives.
• Communicate emerging trends, technologies, and methodologies in data science and analytics through technical assistance, training curricula, and mentoring.
• Explore innovative approaches to address complex public health challenges and improve data analysis capabilities.
• Up to 10% domestic travel may be required.

• Bachelor’s degree or higher in Data Science, Statistics, Epidemiology, or related field. Master’s or PhD in related field preferred.
• Minimum 5 years of relevant professional experience
• Proficiency in programming languages such as Python or R.
• Experience with data manipulation and analysis tools (e.g., SQL, Pandas, Num Py).
• Knowledge of machine learning frameworks (e.g., Tensor Flow, Scikit-learn).
• Experience with data visualization tools (e.g., Tableau, Power BI).
• Strong analytical thinking and problem-solving abilities.
• Ability to interpret complex datasets and derive meaningful insights.
• Excellent verbal and written communication skills.
• Ability to convey technical concepts to non-technical partners effectively.
• Flexibility to adapt to evolving project requirements and priorities.
• Preference given to…