Company
Healthcare
SeniorDataScientist,AudienceAnalyticsforHealthyCommunities
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data Scientist, Audience Analytics for Healthy Communities. Skills: Audience Analytics, Statistical analysis, Machine learning, Data visualization. Develop and maintain data pipelines. Develop and maintain ETL/ELT processes”
What You'll Achieve.
Support analysis; Support reporting; Support decision-making; Generate actionable insights; Ensure accuracy; Ensure consistency; Ensure usability
Industry & Context.
Problem-solving skills
What They're Looking For.
Must Have
5+ years of experience, Master’s degree, Proficiency in Python, R, and SQL, Experience with ETL pipelines, Experience with cloud platforms, Advanced knowledge of statistical and machine learning methods, Experience building dashboards and visualizations
Nice to Have
PhD preferred, Familiarity with audience segmentation, Familiarity with marketing analytics, Familiarity with public health communication, Exposure to GIS tools, Exposure to government/public sector datasets
What You'll Do.
Develop and maintain data pipelines
Develop and maintain ETL/ELT processes
Clean large-scale datasets
Integrate large-scale datasets
Automate large-scale datasets
Build data visualizations
Build interactive dashboards
Conduct advanced statistical analysis
Generate actionable insights
Translate analytical outputs into recommendations
Translate analytical outputs into reports
Translate analytical outputs into presentations
Collaborate to design communication strategies
Collaborate to design audience targeting approaches
Integrate data from multiple vendors
Integrate data from multiple systems
Manage data from multiple vendors
Manage data from multiple systems
Support client engagement activities
Contribute to analytics infrastructure development
Contribute to analytics infrastructure maintenance
Contribute to data visualization frameworks development
Contribute to data visualization frameworks maintenance
How You'll Work.
Team & Collaboration
Campaign teams; Research teams; Technical teams; External stakeholders
Communication Scope
Client-friendly narratives; Presentations; Status updates; Strategic discussions
Full Job Description
## Accountabilities Develop and maintain robust data pipelines and ETL/ELT processes to clean, integrate, and automate large-scale datasets from surveys, media, and campaign performance sources using Python and R. Build and optimize data visualizations and interactive dashboards in tools such as Tableau and Power BI to support analysis, reporting, and decision-making. Conduct advanced statistical analysis, including segmentation, causal inference, predictive modeling, and exploratory data science to generate actionable insights. Translate complex analytical outputs into clear recommendations, reports, and presentations for clients and internal stakeholders. Collaborate with campaign, research, and technical teams to design data-informed communication strategies and audience targeting approaches. Integrate and manage data from multiple vendors and systems, ensuring accuracy, consistency, and usability across platforms. Support client engagement activities including presentations, status updates, and strategic discussions on campaign performance and optimization. Contribute to the development and maintenance of scalable analytics infrastructure and data visualization frameworks. Requirements 5+ years of experience in data science, applied statistics, audience analytics, or related quantitative fields. Master’s degree in Data Science, Statistics, Public Health, Social Sciences, Marketing, or a related discipline (PhD preferred). Strong proficiency in Python, R, and SQL for data processing, modeling, and analysis. Experience with ETL pipelines, data engineering workflows, and cloud platforms such as AWS (e.g., S3, RDS, SageMaker). Advanced knowledge of statistical and machine learning methods including regression models, clustering, random forests, Bayesian methods, and model evaluation techniques. Experience building dashboards and visualizations using Tableau, Power BI, or similar tools. Ability to work with large, complex, and heterogeneous datasets in fast-paced env
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