Clinical Operations Business Intelligence Analyst

Job Title:
Clinical Operations Business Intelligence Analyst

Duration: 6+ Months (with possible to convert fulltime)

Pay Rate: $50/hr.

- $60/hr.

Required Qualifications:

• 3-5 years' experience in business/ data analytics, healthcare analytics, healthcare quality, clinical and operations decision support or related field.
• 1 - 2 years in a lead/senior role.
• Working knowledge of back-end databases (e.g., relational designs) spreadsheets, word processing, statistical software, analytical models, data science principles and application, and data visualization programs (e.g., Tableau, Qlik View, Qliksense, Power BI).
• Knowledge of business (operational, clinical and financial) statistics and data analyses techniques.
• Expert knowledge in Python, R, and/or SQL software programming.
• Ability to manage, analyze, and derive clinical and operational insights from health system information technologies.
• Strong analytical thinking and problem-solving skills.

Demonstrated leadership capabilities, including but not limited to:

• Developing dynamic, constructive working relationships and partnerships with operational and clinical partners.
• Excellent interpersonal skills (negotiation, listening and communication skills) characterized by effective interactions with a diverse range of internal and external constituents, stakeholders and audiences.
• Relationship driven, consultative, a team player, able to effectively lead process improvement initiatives.
• Possesses a good understanding of Business Intelligence tools, technology platforms, and related systems to handle queries about clinical and business data/analytical solutions.
• Be adept at presenting technical materials to a non-technical audience, applying human factors principles and user centered design principles, understanding user workflows, applying statistical methods platforms such as Qlik View and Tableau.

Preferred Qualifications:

• Master's degree (Health Administration, Nursing, Industrial Engineering, Analytics).
• Expertise in data science, including machine learning approaches to produce predictive models.
• Proficiency in statistical approaches.
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• Master level expertise in data visualization platforms such as Qlik View and Tableau.