Data Analyst

Responsibilities:

• Provides a high level of expertise in systems relating to assigned areas.
• Responds to requests for detailed data to support report findings.
• Acts as an advisor or thought partner to a senior executive by structuring undefined issues for resolution, researching issues, and summarizing information, working with relevant stakeholders to provide the executive with the information needed to make sound and timely decisions.
• Develops and maintains strong business relationships with internal business partners, including all levels of management, senior leaders, service chiefs, multiple levels of management, and other data users.
• Performs analysis for problem solving and new methodologies by extracting data using tools such as Oracle SQL Developer, SAS, Python, MS Access and Crystal Reports; and compiling data from KPHC Clarity, telephony, and workforce management data systems.
• Delivers high quality results on time.

Qualifications:

• Bachelors degree in Information System Management, Data Science, Computer Science, or related fields is required; Master’s Degree in related field is desired.
• Highly proficient with SQL, SAS, Python, Tableau and Excel is required.
• Experience with analytical manipulation and interpretation of multiple large databases or data warehouses required.
• Prior healthcare data analysis experience is preferred.
• Oracle Database SQL Certified Associate certification is desired.
• SAS Certified Advanced Programmer for SAS 9 certification is desired.
• SAS Certified Statistical Business Analyst using SAS 9: regression and modeling certification is desired.
• Effective written and verbal communication skills.
• Knowledge of or experience in database programming, data mining, advanced SQL queries, MySQL, Oracle, Tableau, and Python.
• Knowledge of or experience in transitioning various Microsoft Excel Reports containing  to Tableau and building various statistical and predictive models using tools like SAS and python.

Key Skills:

• Data cleaning and preparation.
• Data analysis and exploration.
• Statistical knowledge.
• Creating data visualizations.
• Creating dashboards and reports.
• Writing and communication.
• Domain knowledge.