Role Summary
This Principal Quantitative Data Analyst role will be a key contributor to our data analytics initiatives. You will have the opportunity to work with complex data sets, identify trends, and generate predictive models to support decision-making processes.
About the Role
We are looking for a highly analytical and creative individual who can turn complex data into actionable insights. This role requires a proactive person who can work effectively within a team, think creatively, and develop innovative solutions to complex problems.
Key Responsibilities
* Data Analysis and Reporting: Utilize visualization tools to create, maintain, and optimize interactive dashboards and reports that provide actionable insights into pharmacy operations, patient outcomes, and medication usage.
* Data Management: Collect, clean, and manage large datasets from various sources, ensuring data integrity and accuracy.
* Statistical Analysis: Apply statistical methods to analyze pharmacy data, identify trends, and generate predictive models to support decision-making processes.
* Collaboration: Work closely with cross-functional teams, including pharmacists, IT, and management, to understand data needs and deliver tailored analytical solutions.
* Performance Monitoring: Track and evaluate key performance indicators (KPIs) related to pharmacy operations and patient care, providing regular updates and recommendations for improvement.
Requirements
* Educational Background: Bachelor's or Master's degree in Statistics, Data Science, Pharmacy, or a related field.
* Proven significant experience in data analysis, with a focus on pharmacy data as an advantage.
* Technical Skills: High Proficiency in Power BI development.
* Analytical Skills: Strong analytical and problem-solving skills, with the ability to interpret complex data and generate actionable insights.
* Creativity: Ability to think creatively and develop innovative solutions to complex problems.
* Communication: Excellent verbal and written communication skills, with the ability to present data findings clearly and concisely to non-technical stakeholders.