Senior Data Analyst, Clinical Quality and Product
Omada Health
PythonSQLTableau
Data Analytics Manager
John Hopkins University
full-time
Posted on:
Location: 🇺🇸 United States
Visit company websiteSalary
💰 $73,300 - $128,300 per year
Job Level
SeniorLead
Tech Stack
PythonTableau
About the role
- Lead development and implementation of quantitative data strategies to understand complex business issues.
- Shape and conduct approaches for collecting, organizing, and analyzing data, including creating new data (e.g., surveys).
- Employ diverse quantitative methodologies and software (data validation, joining datasets, trend analysis, GIS mapping, regression, etc.).
- Invent and iterate novel solutions to data problems.
- Create and manage project plans for quantitative data components.
- Develop and manage partnerships with data providers and stakeholders.
- Champion quantitative data-driven decision making.
- Produce compelling data visualizations (Tableau, Power BI) and communicate findings to non-technical audiences.
- Develop metrics and measurement systems to assess project impact.
- Connect data insights to research; collaborate on focus groups, interviews, user testing; support literature reviews.
- Serve as key participant in data methodology and lead the data analytics team; may manage Data Analysts.
- Manage, clean, and analyze large administrative and claims datasets; support statistical analyses and manuscript drafting.
- Provide mentorship to graduate students and research assistants; minimal travel for conferences/meetings.
Requirements
- Bachelor's Degree.
- Seven years of experience.
- Additional education may substitute for required experience per JHU equivalency formula.
- Additional related experience may substitute for required education beyond a high school diploma/equivalent.
- PhD in epidemiology, demography, or related field preferred.
- 5 or more years experience supporting or leading research on related topics preferred.
- Content area expertise in reproductive and perinatal epidemiology preferred.
- Extensive experience working with claims data and vital statistics data preferred.
- Strong publication record preferred.
