Data Scientist

Bachelor’s degree or higher in Data Science, Statistics, Epidemiology, or a related field required; Master’s degree or PhD in a related field preferred.

Minimum of five (5) years of relevant professional experience in data science, analytics, epidemiology, or a related discipline.

Proficiency in data visualization tools, including Power BI.

Proficiency in ArcGIS software suites for geospatial analysis and mapping.

Proficiency in statistical analysis software, including SAS.

Proficiency in programming languages such as Python and/or R.

Experience using data manipulation and analysis tools, including SQL.

Experience applying Natural Language Processing (NLP) techniques for text classification, information extraction, or related applications, preferably involving healthcare or public health datasets.

Experience with cloud-based data warehouses, such as Snowflake, and cloud platforms, including Amazon Web Services (AWS) and Microsoft Azure, preferred.

Experience with small area estimation techniques, Bayesian hierarchical models, and/or multilevel modeling.

Strong analytical thinking and problem-solving skills with the ability to identify and address complex challenges.

Demonstrated ability to interpret complex datasets and translate findings into meaningful, actionable insights.

Excellent verbal and written communication skills.

Ability to effectively communicate technical concepts and analytical findings to non-technical stakeholders and partners.

Ability to adapt to changing priorities, project requirements, and organizational needs.

Professional certifications in Data Science, Machine Learning, Public Health Analytics, or related fields preferred.

Outstanding interpersonal and teamwork skills, with the ability to build and maintain productive relationships with colleagues, stakeholders, and external partners.

Demonstrated ability to work effectively both independently and as part of a collaborative team environment.

Experience working in virtual environments and collaborating with remote teams and partners.

Proficiency in Microsoft Office Suite, including Word, Excel, PowerPoint, and Outlook.

Develop, implement, and enhance data analysis and visualization tools that provide timely, relevant information to support decision-making related to public health, including outbreak response, disease surveillance, and emergency preparedness.

Analyze diverse public health datasets to identify trends, patterns, and correlations.

Apply statistical methods and machine learning algorithms to generate actionable insights.

Develop predictive models to forecast disease patterns, assess risk factors, and inform intervention strategies.

Utilize advanced statistical modeling techniques to produce reliable and precise estimates for small populations and sparsely populated rural regions.

Build and maintain interactive dashboards to support real-time public health surveillance.

Provide geospatial analysis support for infectious disease surveillance and epidemiologic investigations.

Apply Natural Language Processing (NLP) techniques to unstructured data to automate data processing and enhance case detection capabilities.

Continuously evaluate and optimize algorithms to improve performance, accuracy, and efficiency.

Create compelling data visualizations and reports that effectively communicate findings to stakeholders and decision-makers.

Present complex data-driven insights in a clear, concise, and understandable manner to support informed decision-making.

Collaborate with public health organizations and external partners to identify data needs, establish objectives, and deliver analytical solutions.

Provide analytical support and evidence-based recommendations to guide public health policies, programs, and initiatives.

Remain current on emerging trends, technologies, and best practices in data science, analytics, and public health informatics.

Explore innovative approaches to address complex public health challenges and strengthen organizational data analysis capabilities.

Provide training and technical assistance to epidemiologists and public health staff in data visualization, geospatial analysis, and statistical analysis using tools such as Power BI, ArcGIS, and SAS, enhancing their ability to analyze, interpret, visualize, and communicate epidemiologic data.