Sr Data Scientist

Job Overview

At Keurig Dr Pepper (KDP), the Data & Decision Science (DDS) team builds scalable data products that power decision‑making across e‑commerce, revenue growth management, supply chain, finance, and commercial strategy.

Build Modern Data & ML Infrastructure

• Architect and scale robust cloud‑based data pipelines supporting advanced analytics and machine learning use cases.
• Design and optimize data warehouses and reporting marts using dimensional modeling best practices.
• Integrate new internal and external data sources aligned to evolving business strategies.
• Establish monitoring, logging, and data quality frameworks to ensure reliability and accuracy at scale.
• Develop and orchestrate ETL/ELT workflows using Apache Airflow or comparable orchestration tools.

Operationalize & Learn Data Science Foundations

• Partner with data scientists to product ionize models across batch and near real‑time workflows.
• Expand your expertise in Python‑based data science fundamentals, including feature engineering, model pipelines, and statistical workflows.
• Implement version‑controlled, repeatable ML pipelines with CI/CD principles.
• Support model lifecycle management, feature store integration, and performance monitoring.

Make Our Data AI‑Ready

• Design data structures and pipelines that enable AI and advanced analytics applications.
• Improve metadata management, data lineage, and semantic consistency to support future generative and predictive AI initiatives.
• Influence enterprise standards for structured, high‑quality, and well‑governed data.
• Ensure our cloud infrastructure (Snowflake, Big Query, Azure, etc.) is optimized for scalable AI workloads.

Strengthen Governance & Self‑Service

• Develop and maintain architecture documentation, source‑to‑target mappings, and data dictionaries.
• Enhance reporting marts and semantic layers to enable trusted self‑service analytics.
• Implement automated data validation and monitoring to reduce errors and increase stakeholder confidence.

Provide Technical Leadership

• Mentor engineers and collaborate across cross‑functional teams.
• Translate complex business requirements into scalable, sustainable technical solutions.
• Drive modernization of legacy systems and improve enterprise data processes.
• Influence data strategy with a long‑term, systems‑oriented mindset.

• 10+ years of experience in data engineering, analytics engineering, or enterprise data architecture.
• Proven experience designing and managing enterprise data warehouses and dimensional data marts.
• Strong SQL expertise and experience with Snowflake, Big Query, Azure Synapse, or equivalent platforms.
• Experience with ETL/ELT tools (Informatica, SSIS, Talend, Data Stage, Azure Data Factory, etc.).
• Exposure to or interest in learning Python for data science and ML workflows.
• Familiarity with orchestration tools such as Apache Airflow (or willingness to deepen expertise).
• Experience implementing governance artifacts and improving enterprise data quality.
• Strong understanding of BI/reporting ecosystems (Power BI, Analysis Services, Cognos, etc.).
• Demonstrated ability to lead engineers and deliver measurable business value.
• Ability to connect technical architecture decisions to strategic business outcomes.

• Experience supporting ML deployment or working alongside data science teams.
• Exposure to consumer, retail, or CPG datasets.
• Experience preparing enterprise data environments for AI and advanced analytics use cases.

• Salary Range: $76,400 - $140,000 (actual placement may vary based on experience, skills, and other factors).
• Benefits:
  Medical, Dental, Vision, Disability, Paid Time Off (including paid parental leave, vacation, and sick time), 401(k) with company match, Tuition Reimbursement, and Mileage Reimbursement.
• Annual bonus based on performance and eligibility.

KDP uses artificial intelligence to assist with initial resume screening and candidate matching. This technology helps us efficiently identify candidates whose qualifications align with our open roles. AI does not make hiring decisions; all decisions throughout the hiring process are made by talent acquisition team members. If you prefer not to have…