Principal Data Scientist, Marketing Analytics

Keurig Dr Pepper Inc.; Burlington (MA); Hybrid; USD 97,000 - 169,000; Full time

Benefits offered by this job

Medical

Dental

Vision

401k with company match

Tuition Reimbursement

Mileage Reimbursement

Annual bonus

Job summary

Keurig Dr Pepper Inc. seeks a Principal Data Scientist, Marketing Analytics, to lead a cross-functional team at the intersection of marketing data science, data engineering, and AI.

This role designs and operationalizes advanced analytics, measurement, and data integrations to enable smarter marketing decisions and scalable analytics products. Hybrid work model with in-office Tuesdays, Wednesdays, and Thursdays; reports to Senior Director of Marketing Analytics; manages a Marketing Data Science

Qualifications

• 8+ years of experience in Data Science, Analytics, or related technical disciplines.
• Advanced proficiency in Python and SQL; building scalable analytics solutions.
• Experience with cloud platforms (Snowflake, Databricks, AWS, Azure, GCP).
• Experience developing APIs and data integrations.
• Strong ability to translate business needs into scalable technical solutions.

Responsibilities

• Define the roadmap for marketing measurement, analytics, automation, and AI use cases.
• Design scalable analytics solutions and data products for marketing decisions.
• Lead API development and data integrations with cross-functional teams.
• Mentor and manage a Marketing Data Science Analyst.
• Collaborate with Enterprise Data Science to align standards and governance.
• Advocate reusable analytics assets and best practices.

Skills

Python

SQL

Tools

Snowflake

Databricks

AWS

Azure

GCP

Job description

*Position is hybrid. Tuesday, Wednesday, and Thursday are required in office days*

We are seeking a Principal Data Scientist, Marketing Analytics, to serve as the dedicated technical leader within the Marketing Analytics team. This role will design and operationalize advanced analytics, measurement, data integration, and AI capabilities that enable smarter marketing decisions.

This role will report to the Senior Director of Marketing Analytics and will partner closely with Enterprise Data Science to align on technical standards, leverage enterprise capabilities where appropriate, and ensure marketing-specific analytics priorities are delivered in a scalable and sustainable way.

This role sits at the intersection of Marketing Analytics, Data Science, Data Engineering, and Artificial Intelligence. The ideal candidate combines deep technical expertise with strong business acumen and will partner closely with Marketing, Media, Technology, Data Management, Enterprise Data Science, and external partners to transform complex marketing data into scalable measurement solutions, analytics products, and actionable business insights.

The role will directly manage a Marketing Data Science Analyst and help advance the technical capabilities, processes, and analytical solutions that support the Marketing Analytics function.

Why This Role Matters

Marketing Analytics is evolving from reporting and hindsight analysis to a more scalable decision system that connects data, technology, measurement, and AI. This role ensures the team has dedicated technical leadership to execute marketing-specific priorities while remaining aligned with enterprise data science standards, platforms, and best practices.

As the dedicated technical lead within Marketing Analytics, this individual will shape analytical solutions, technical approaches, and scalable capabilities that help marketing leaders make better investment, audience, measurement, and optimization decisions.

Key Responsibilities:

Technical Leadership & Capability Development

• Serve as the technical leader for Marketing Analytics, helping define the roadmap for marketing measurement, advanced analytics, automation, and AI use cases.
• Design and develop scalable analytics solutions, data products, and automation frameworks that improve marketing decision-making.
• Translate complex business challenges into technical solutions and analytical approaches, balancing rigor with practical execution.
• Define and implement best practices for marketing analytics engineering, data science, experimentation, AI adoption, and solution development within Marketing Analytics.

Data Integration & Marketing Data Enablement

• Partner with Technology, Data Engineering, and vendor teams to onboard, integrate, and operationalize new marketing, media, customer, and consumer data sources.
• Lead technical implementation of APIs, direct data shares, clean room integrations, cloud-based data connections, and scalable analytics workflows.
• Work across platforms and technologies including Snowflake, cloud environments, marketing technology systems, identity solutions, and clean room ecosystems.
• Improve accessibility, reliability, automation, and usability of marketing data assets that support measurement and decision-making.

Advanced Analytics, Measurement & AI

• Develop advanced analytical solutions to evaluate marketing effectiveness across paid, owned, and earned channels.
• Apply methodologies such as experimentation, incrementality testing, attribution, customer analytics, forecasting, predictive modeling, and marketing mix analysis.
• Identify opportunities to use AI, machine learning, and generative AI to improve marketing effectiveness, efficiency, insight generation, and decision support.
• Develop proof-of-concepts and scalable solutions; partner with technology teams to ensure solutions are secure, sustainable, and aligned with enterprise standards.

Enterprise Data Science Partnership & Collaboration

• Partner closely with Enterprise Data Science, Data Engineering, and Technology teams to align on technical standards, governance, architecture, and best practices.
• Leverage enterprise platforms, tools, and capabilities while serving as the dedicated technical lead for Marketing Analytics priorities and initiatives.
• Identify opportunities to apply, extend, and operationalize enterprise data science capabilities within marketing measurement, analytics, and AI use cases.
• Act as a bridge between Marketing Analytics and Enterprise Data Science teams, helping align marketing priorities with broader enterprise analytics and data strategies.
• Directly manage and mentor a Marketing Data Science Analyst, providing technical leadership, coaching, and career development support.
• Promote knowledge sharing, reusable approaches, and best practices across Marketing Analytics and enterprise Data Science.
• Help shape team processes and operating models that enable efficient execution and scalable delivery without duplicating enterprise-level capabilities.

What You Won't Be Doing

• Operating as a standalone or separate enterprise data science organization.
• Serving as a pure reporting or dashboard owner.
• Working in isolation from Enterprise Data Science, Technology, or Data Engineering teams.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Total Rewards:

• Salary Range: $96,800 - $169,000
• Actual placement within the compensation range may vary depending on experience, skills, and other factors
• Benefits, subject to election and eligibility: Medical, Dental, Vision, Disability, Paid Time Off (including paid parental leave, vacation, and sick time), 401k with company match, Tuition Reimbursement, and Mileage Reimbursement
• Annual bonus based on performance and eligibility

Requirements:

• 8+ years of experience in Data Science, Analytics Engineering, Marketing Analytics, Data Engineering, or related technical disciplines.
• Advanced proficiency in Python and SQL; experience building scalable analytical workflows and technical solutions.
• Experience working with cloud-based data environments and modern data platforms such as Snowflake, Databricks, AWS, Azure, or GCP.
• Experience developing APIs, data integrations, data models, and reusable analytics assets.
• Experience applying machine learning, statistical modeling, experimentation, and predictive analytics techniques to business problems.
• Strong experience working with customer, marketing, media, or consumer data.
• Demonstrated ability to translate business needs into scalable technical solutions and influence cross-functional stakeholders.
• Ability to explain technical concepts and analytical findings clearly to senior business leaders and non-technical audiences.

Keurig Dr Pepper (Nasdaq: KDP) is a leading beverage company with more than 150 owned, licensed and partner brands that meet a wide range of needs and occasions. Our North American refreshment beverage business holds leadership positions across carbonated soft drinks, water, juice and mixers with a portfolio of iconic brands such as Dr Pepper®, Canada Dry®, Mott’s®, A&W®, Peñafiel®, GHOST®, 7UP®, Snapple®, Clamato® and Core Hydration®. Our global coffee business spans more than 100 markets and includes the leading Keurig® single‑serve brewing system in the U.S. and Canada, along with powerhouse brands such as Peet’s, L’OR and Jacobs, and other regional coffee leaders. Our more than 50,000 employees aim to enhance the experience of every beverage and coffee occasion while making a positive impact for people, communities and the planet.

We strive to be an employer of choice, providing a culture and opportunities that empower our team to grow and develop. We offer robust benefits to support your health and wellness as well as your personal and financial well-being. We also provide employee programs designed to enhance your professional growth and development, while ensuring you feel valued, inspired and appreciated at work.

Whatever your area of expertise, at KDP you can be a part of a team that’s proud of its brands, partnerships, innovation and growth. Will you join us?

Keurig Dr Pepper is an equal opportunity employer and recruits qualified applicants and advances in employment its employees without regard to race, color, religion, gender, sexual orientation, gender identity, gender expression, age, disability or association with a person with a disability, medical condition, genetic information, ethnic or national origin, marital status, veteran status, or any other status protected by law.