Data Analyst

Job Description

About Keurig Dr Pepper:

Keurig Dr Pepper (KDP) is a leading North American beverage company boasting a portfolio of over 125 owned, licensed, and partner brands. Their strong distribution network allows them to offer a wide variety of beverages to consumers anytime, anywhere. KDP operates with a unique business model and a top-tier brand portfolio, supported by a dedicated and engaged team. They are known for their work with major beverage brands and the #1 single-serve coffee brewing system in North America. The company emphasizes a fun and collaborative work environment. KDP combines hot and cold beverage offerings at scale, creating a leading presence in the North American market. They aim to be an employer of choice, offering growth opportunities and comprehensive benefits to their approximately 28,000 employees. Keurig Dr Pepper is an equal opportunity employer committed to diversity and inclusion.

Job Description: Data Analyst

Keurig Dr Pepper seeks a Data Analyst to leverage data for solving defined business problems. This role involves interpreting and analyzing moderately complex datasets to provide actionable insights and facilitate data-driven decision-making. The successful candidate will collaborate with engineers, modelers, and executives, gathering and transforming data, performing statistical analyses, and creating visualizations and reports. The goal is to uncover trends, patterns, and opportunities that drive key business initiatives. The company encourages applicants with a passion for data and a desire to use analytics for strategic decisions, particularly those interested in exploring AI, including generative AI techniques.

Responsibilities:

• Use data to answer business questions, solve problems, and inform decisions.
• Gather and clean data from diverse sources, ensuring data integrity and adhering to information governance practices.
• Interpret data using various techniques, from simple aggregation to more complex statistical analysis and modeling (learning and growth in this area is expected).
• Apply statistical methods to identify patterns, trends, correlations, and anomalies, extracting meaningful insights.
• Develop and maintain dashboards, databases, reports, and visualizations to effectively communicate data findings.
• Define KPIs and metrics to track and measure business/IT performance.
• Collaborate with data engineers and IT to optimize data collection, storage, and retrieval.
• Monitor data quality, identifying issues and proposing solutions.
• Stay current on industry trends in data analysis, visualization, and reporting.

Qualifications:

• Bachelor’s degree in data science, statistics, mathematics, information science, or a related field, or equivalent experience.
• 3-5 years of experience as a data analyst, data scientist, BI analyst, or similar role.
• Preferred: Proven experience with SQL, Python, and R for data manipulation and analysis.
• Preferred: Experience with data visualization tools like Tableau, Power BI, and Excel.
• Preferred: Experience with AI or machine learning, including generative AI, for data analysis or solution development.
• Experience working with diverse technologies and processing environments.
• Native-level English proficiency.

Skills:

• Basic understanding of data models, structures, database design tools, and query languages (e.g., Visio, SQL).
• Basic knowledge of data exploration techniques (binning, pivoting, summarizing, correlation analysis).
• Basic understanding of statistical software (R, Python, SAS) and statistical analysis techniques (descriptive and inferential statistics).
• Skills in data aggregation, standardization, interpretation, and modeling. Ability to identify and resolve data quality issues.
• Ability to identify patterns, understand database design, and participate in database project planning.
• Skills in leveraging tools to analyze large datasets, identifying patterns and relationships to solve business problems.
• Developing skills in using relational database management systems.
• Attention to detail and ability to maintain data accuracy and integrity.
• Ability to translate data insights into actionable recommendations for stakeholders.
• Strategic thinking and ability to make decisions based on value delivered.