Sort by
Refine Your Search
-
experience in robust data analysis, data storage, and data transfer. Experience with PL/SQL and managing large data feeds and data validation. Experience using visual analytics software such as Power BI
-
Questionnaires, Body Weights). · Data analysis and visualization skills (Power BI, Excel, R, Python, etc.). · Previous interdisciplinary work and communication within a comprehensive high-performance environment
-
with data‑sharing plans. Prepare tables, visualizations, lay summaries, and progress reports for PIs and stakeholders. Support qualitative or statistical analysis using tools such as SAS, R, SPSS, NVivo
-
, and ensure deliverables are completed successfully. - Prepare reports for funders, compliance, and internal review. Data Analysis & Visualization – 20% - Compile, analyze, and interpret quantitative and
-
are highly proficient in financial modeling and data analysis techniques. You are inherently driven to achieve goals, and you continually pursue process improvement. You are a self-starter and you
-
, public health, or related technical field. Experience - 5+ years of experience in business systems analysis, data analytics, or business intelligence. Proficiency in data visualization tools (e.g., Tableau
-
the collection, compilation, documentation, and analysis of clinical research data. May oversee the work of junior staff and train or mentor others in clinical research tasks. Provides and documents professional
-
, or engineering. Preferred Qualifications: The ideal candidate will bring experience or a very strong foundational understanding in areas such as high‑dimensional data analysis and translational research, and must
-
and collaborators. Creates clear visualizations to help communicate key information to stakeholders. Uses statistical tools (e.g. SAS, R, SPSS) to perform statistical analysis. Codes data using
-
for direct marketing and annual giving. Create reporting mechanisms using existing platforms and identifying new solutions to meet reporting needs. Synthesize data analysis into clear, relevant, and visually