This position embodies the Memorial Health System Performance Excellence Standards of Safety, Courtesy, Quality, and Efficiency that support our mission, vision and values. These standards are evident in the daily work, which includes the following:
- Works with teams to discover insights from analyzing operational, financial, quality, and peer comparison data.
- Under direct supervision, models complex business problems, discovers business insights and identifies opportunities through the use of statistical, mathematical, algorithmic, data mining and visualization techniques.
- Proficiency in integrating and preparing large, varied datasets, architecting specialized database and computing environments, and communicating results.
- Works closely with subject matter experts and technical experts to understand proper data extraction and interpretation.
Requirements for this position include:
- Bachelor’s degree or higher in the studies of Data Analytics, Statistics, Mathematics, Computer Science or other related field
- Completion of the MHS Lean Six Sigma Green Belt curriculum is required within 2 years of job placement.
- 1-3 years’ experience in data analysis, operations improvement work, computer science/business intelligence work, or other related experience.
- Must have strong problem solving skills with a keen drive to learn about and explore datasets.
- Understanding of application and interpretation of statistical tools such as Hypothesis Testing, Non-Parametric Tests, Analysis of Variation, Various forms of Regression and factor analysis, as well as various forecasting and prediction techniques.
- Basic understanding of Structured Query Language (SQL) code to process and ETL techniques for extracting data from systems and transforming that data into the forms necessary for analysis.
- Experience with statistical computer packages (Minitab, SPSS, SAS) to manipulate data and draw insights from large data sets.
- Basic understanding of relational database (RDB) systems and how to explore various data architectures using standard tools (Ex: Microsoft SQL Management Studio, Oracle SQL Developer, etc.).
- Basic understanding of data mining concepts.