JOB OVERVIEW:

Keurig Dr Pepper is seeking a Data Analyst who can work with data to solve defined business problems. The Data Analyst will interpret and analyze moderately complex datasets to provide insights and support data-driven decision making within the organization. This position will work alongside engineers, modelers, and business executives to gather and transform data, conduct statistical analyses, and create visualizations and reports that will contribute to identifying trends, patterns, and opportunities that drive business initiatives.
If you are a data enthusiast with a desire to leverage analytics to drive strategic decisions and are eager to explore new frontiers with AI—including generative AI techniques—we encourage you to apply and become part of our dynamic, innovative team!

MINIMUM QUALIFICATIONS/REQUIREMENTS:

• Bachelor’s degree in data science, statistics, mathematics, information science, or related field, or equivalent combination of education and work experience.
• Typically, 3–5 years of experience as a data analyst, data scientist, BI analyst, or related profession.
• Proven experience with programming languages such as SQL, Python, and R for data manipulation and analysis. (preferred)
• Proven experience with data analysis and visualization tools such as Tableau, Power BI, and Excel. (preferred)
• Experience with AI or machine learning techniques—including generative AI frameworks—for data analysis, modeling, or solution development. (preferred)
• Experience working with multiple, diverse technologies in various processing environments.
• Native-level proficiency/fluent in English.

As the Data Analyst, you will…

• Discover how data can be used to answer questions, solve problems, and support business decisions.
• Complete the gathering and cleaning processes for data from various sources, ensuring data integrity and quality by adhering to and applying information governance practices.
• Interpret results using a variety of techniques, ranging from simple data aggregation to learning to apply more complex statistical analysis and modeling. Learn and grow skills related to using statistical methods and techniques to identify patterns, trends, correlations, and anomalies, and extract meaningful insights.
• Develop and maintain dashboards, databases, tables, reports, views, and visualizations to communicate data findings effectively.
• Identify KPIs and develop metrics to track and measure business/IT performance.
• Collaborate with data engineers and IT professionals to optimize data collection, storage, and retrieval processes.
• Monitor data quality to identify data issues and propose data cleansing or enhancement solutions.
• Stay updated with industry trends and best practices in data analysis, visualization, and reporting.