● 4+ years of experience in data analysis using python and SQL. ● Advanced experience with python for data analysis, especially using pandas. This includes the ability to write production-quality code in collaboration with a team. ● Advanced SQL skills. This includes the ability to write production-quality SQL code that is performant and maintainable. ● Experience using git to contribute to a shared repository with coworkers on the same project. This includes the ability to perform basic git command line operations. ● Strong communication skills with the ability to present insights to technical and non- technical audiences, including leadership. ● Familiarity with principles of frequentist statistics, e.g. power, statistical significance. Nice to Have Skills & Experience ● Familiarity with basic principles of bayesian statistics, e.g. posteriors. ● Familiarity with basic principles of machine learning, e.g. measures of error. ● Experience working with healthcare data, specifically prescriptions. Job Description Day to Day Responsibilities : The Senior Analyst of Pricing Optimization will build analytical tooling and perform data analysis to support GoodRx’s AI-driven Pricing Optimization function. This individual will work closely with data scientists and machine learning engineers to understand the performance of GoodRx’s pricing models and identify areas of weakness, and also communicate directly with leadership regarding the results of experiments. The Senior Analyst will be a key thought partner for the Pricing Optimization team, helping guide the future of AI-based pricing at GoodRx Responsibilities ● Develop tooling to facilitate automated self-service analysis of pricing tests. This will involve writing production-quality python and SQL. ● Perform root cause analyses of experiment performance to identify opportunities for improvement in model performance. ● Communicate complex analyses and recommendations clearly and concisely to stakeholders and leadership. ● Collaborate cross-functionally with data science, product management, and business stakeholders to scope and prioritize analytical work