PBM Data Analyst

Data Analyst - Pharmacy Benefit Management (PBM) Job Summary: We are seeking a highly motivated and experienced Data Analyst with a strong focus on Pharmacy Benefit Management (PBM) to join our growing team. The ideal candidate will possess deep expertise in analyzing PBM data, including claims data, drug pricing, and demographics. This role will play a critical part in supporting business decisions and driving data-driven insights within the PBM domain. Responsibilities: Conduct in-depth analysis of PBM data, including claims data, drug utilization, pricing trends, and demographic information. Develop and maintain complex SQL queries to extract, transform, and load data from various sources. Proficiently utilize SAS for data analysis and reporting. Leverage analytical skills to identify trends, patterns, and anomalies within the PBM data. Prepare comprehensive data reports and presentations to communicate findings to stakeholders. Develop and maintain data dashboards using tools such as Tableau, Power BI, or Qlik. Collaborate with business stakeholders to understand their data needs and translate them into actionable insights. Stay abreast of industry trends and best practices in PBM data analysis. Experience with Python is a significant plus. Qualifications: Bachelor's degree in Data Science, Statistics, Mathematics, Economics, or a related field preferred. 4+ years of experience in data analysis within the PBM industry. Proven experience with PBM carriers. Strong proficiency in SQL, with experience in writing complex queries and performing data manipulation. Expertise in SAS for data analysis and reporting. Advanced Excel skills, including data manipulation, pivot tables, and advanced formulas. Experience with data visualization tools such as Tableau, Power BI, or Qlik. Excellent analytical, problem-solving, and communication skills. Strong attention to detail and accuracy. Ability to work independently and as part of a team. Preferred Qualifications: Experience with Python for data analysis and machine learning. Experience with cloud-based data platforms (e.g., AWS, Azure, Google Cloud). Knowledge of healthcare data standards (e.g., NCPDP, HIPAA).

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