Data Analyst at WCIRB leveraging SQL, R or Python to support California’s workers’ compensation system. Assisting with analytics to provide insights in medical cost trends and classification.
Responsibilities
Assist with the implementation of medical and classification analytics projects through:
Independently developing well-documented and reproducible scripts in SQL, R or Python for pulling and wrangling data for the Analyst’s own work and for the use of research staff in studies or to address ad-hoc requests
Performing accuracy and reasonableness checks to assure quality of the working dataset is appropriate to each study
Communicating clearly to research staff the rules employed to prepare the working datasets for study
Assisting with statistical analyses (e.g., hypothesis testing, regression analysis, predictive modeling) to answer key research questions
Developing data visualization to effectively highlight trends and patterns
Preparing tables and figures to present analysis results in reports and presentations
Assuring analysis results are accurate following the Data Analytics team review protocol
Providing technical and peer review of other analysts’ work
Communicating results via written and oral presentations
Develop and maintain automation of routine analysis data and reporting tasks, including annual and quarterly medical benchmarking reports
Interact and communicate with representatives of other units of the WCIRB on various analytics-related and operational projects and issues.
Requirements
Bachelor’s Degree or above in a quantitative field such as statistics, economics, data science, computer science or other related field
A minimum of two years of SQL, R or Python programming experience in a Data Analyst or equivalent role, or through coursework
Demonstrated knowledge of the U.S. healthcare system, U.S. industry classifications or property/casualty insurance obtained through work or internship experience
Strong proficiency in data wrangling, building functions and producing data visualization in R or Python
Track record of completed analytical projects in R or Python
Experience with statistical modeling (e.g., regression analysis), text analytics, geospatial data or predictive modelling
Experience in working with relational databases, large data sets and multiple data sources
Ability to communicate both effectively and professionally, both verbally and in writing
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