Data Analyst

Job Description

About Keurig Dr Pepper:

Keurig Dr Pepper (KDP) is a major beverage company in North America, boasting a portfolio of over 125 owned, licensed, and partner brands. Their strong distribution network allows them to offer a wide variety of beverages for all occasions. They operate using a distinct business model and possess a top-tier brand portfolio, supported by a dedicated and engaged workforce committed to their company values. KDP is known for its popular brands and the #1 single-serve coffee brewing system in North America. The company emphasizes a collaborative and fun work environment. They’ve successfully combined hot and cold beverage offerings at a large scale. KDP aims to be a preferred employer, providing a supportive culture and development opportunities for its approximately 28,000 employees. They offer a comprehensive benefits package encompassing health, wellness, financial well-being, and professional growth initiatives. Keurig Dr Pepper is an equal opportunity employer committed to diversity and inclusion.

Job Description: Data Analyst

Keurig Dr Pepper is searching for a Data Analyst to tackle defined business challenges using data. This role requires interpreting and analyzing moderately complex datasets to provide insights and facilitate data-driven decision-making. The Data Analyst will collaborate with engineers, modelers, and executives, engaging in data gathering, transformation, statistical analysis, and the creation of visualizations and reports. The goal is to identify trends, patterns, and opportunities to advance business initiatives. The ideal candidate is a data enthusiast eager to leverage analytics for strategic decision-making and explore AI, including generative AI techniques.

Responsibilities:

• Utilize data to answer questions, solve problems, and support business decisions.
• Gather and cleanse data from diverse sources, ensuring data integrity and quality through information governance practices.
• Interpret data using various methods, from basic aggregation to more advanced statistical analysis and modeling.
• Develop skills in applying statistical techniques to identify patterns, trends, correlations, and anomalies, and extract meaningful insights.
• Develop and maintain dashboards, databases, tables, reports, views, and visualizations to effectively communicate findings.
• 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.
• Monitor data quality, identifying issues and proposing solutions for cleansing or enhancement.
• Stay current with industry trends and best practices in data analysis, visualization, and reporting.

Qualifications:

• Bachelor’s degree in data science, statistics, mathematics, information science, or a related field (or equivalent experience).
• Typically 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 analysis and visualization tools like Tableau, Power BI, and Excel.
• Preferred: Experience with AI or machine learning techniques (including generative AI) for data analysis, modeling, or solution development.
• Experience working with various technologies and processing environments.
• Native-level English proficiency.

Required 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 (e.g., R, Python, SAS) and analysis techniques (descriptive and inferential statistics).
• Ability to aggregate, standardize, interpret, and model data; identify and resolve data inaccuracies.
• Ability to identify patterns, understand database design, and participate in database project planning.
• Ability to leverage tools and techniques to analyze large datasets, identify patterns, and solve business problems.
• Developing skills in using relational database management systems.
• Ability to maintain data accuracy and integrity, with attention to detail.
• Ability to translate data insights into recommendations for stakeholders.
• Ability to think strategically and make value-based decisions.