Data Scientist

CDC Foundation

11d•Remote

About The Position

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 Minnesota Department of Health, Health Promotion and Chronic Disease Division, the Data Scientist will utilize advanced analytics, statistical techniques, and machine learning algorithms to derive insights that support public health efforts. The Minnesota Department of Health (MDH) and the Collaborative for Rural Public Health Innovation (CRPHI) are partnering to advance data modernization effort to enhance the functionality, interoperability, and timeliness of public health data systems, focusing on chronic disease (CD) data. This role will engage with CRPHI partners to translate and adapt CD syndromic surveillance (SynS) case definitions (developed by another data scientist) into tools and visualizations that resonate with and support rural local public health strategy and surveillance activities. They will lead development of workflows supporting CD SynS data sharing between MDH and CRPHI (and other rural health departments) that are integrated into a suite of CD data. Examples of the types of conditions of interest for case definition development include: heart attack, stroke, asthma, dental emergencies, and others. The Data Scientist will be hired by the CDC Foundation and assigned to the Minnesota Department of Health, Health Promotion and Chronic Disease Division. This position is eligible for a fully remote work arrangement for U.S. based candidates.

Requirements

Bachelor’s degree or higher in Data Science, Informatics, Statistics, or related field.
Minimum 5 years of relevant professional experience.
Proficiency in programming languages R. (required), Python (nice to have).
Experience with data manipulation and analysis tools (e.g., SQL, Pandas, NumPy).
Experience with data visualization tools, especially Power BI, R-Shiny, and Excel) to display data and support easy data sharing through downloads.
Experience with databases (e.g., Amazon Athena, MongoDB).
Familiarity with GIS systems (e.g., ArcGIS, DAX).
Experience or familiarity with HL7 ADT message requirements, specifications, and structure.
Strong analytical thinking and problem-solving abilities.
Ability to work with teams to interpret complex datasets and derive meaningful insights.
Excellent verbal and written communication skills.
Ability to convey technical concepts related to data science and informatics to non-technical partners and epidemiologists looking to learn effectively.
Flexibility to adapt to evolving project requirements and priorities.
Strong interpersonal and teamwork skills; collegial; energetic; and able to develop productive relationships with colleagues, partners, and partners.
Demonstrated ability to work well independently and within teams.
Experience working in a virtual environment with remote partners and teams.
Proficiency in Microsoft Office.

Nice To Haves

Master’s or PhD in related field preferred.
Knowledge of machine learning frameworks (e.g., TensorFlow, Scikit-learn), not required, but preferred.
Professional certifications in data science, machine learning, or public health analytics preferred.

Responsibilities

Develop, implement, and improve data analysis and visualization tools for use by organization staff, to provide timely, relevant information that informs decisions affecting the public’s health.
Apply statistical methods and machine learning algorithms to extract actionable insights.
Utilize existing syndromic surveillance data tools such as ESSENCE for chronic disease definition algorithm design and testing.,
Adapt algorithms for use within Minnesota-based syndromic surveillance data repositories.
Continuously optimize tools for enhanced accuracy and performance, with guidance from MDH and CRPHI team.
Create 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.
Adapt data products to meet the varying needs of CRPHI and rural agency partners.
Engage productively with cross-disciplinary teams.
Stay abreast of emerging trends, technologies, and methodologies in data science and analytics.
Explore innovative approaches to address complex public health challenges and improve data analysis capabilities.
Up to 10% domestic travel may be required.