Manager, Customer Analytics and Decision Science

PepsiCo • Plano, TX

2d

About The Position

The Customer Analytics and Decision Science Manager is part of PepsiCo’s North America Insights & Intelligence Data and Analytics team. The role turns shopper, store, product, and customer data into scalable insights and tools that guide assortment, space planning, segmentation, go-to-market decisions, shopper activation, personalization, and commercial planning. The manager develops strategies and analytical processes and delivers insights that support PepsiCo teams and retail partners across the United States.

This position partners across business, analytics, product, data, and engineering teams to translate business needs into technical requirements and deliver trusted solutions with measurable impact. It also shapes the roadmap and ongoing improvement of Store DNA (sDNA) and related tools, ensuring analytical quality, enabling users to apply solutions, and tracking business value through adoption, speed to insight, data quality, user satisfaction, and use-case deployment.

Requirements

• Bachelor’s degree in data science, computer science, statistics, business analytics, marketing analytics, economics, or a related field.
• At least 5 years of experience in analytics, commercial analytics, data or decision science, business intelligence, data product delivery, or a related field.
• Expert-level SQL skills, including extracting, joining, aggregating, validating, and troubleshooting data from large and small data sets.
• Strong Python skills and experience with pandas or comparable analytics tools for developing, validating, and scaling repeatable analyses.
• Experience building, launching, or supporting analytics solutions, dashboards, decision-support tools, or data products used by business teams.
• Ability to translate business questions into analytical approaches, technical requirements, and practical recommendations for commercial stakeholders.
• Experience applying artificial intelligence and machine learning tools to enhance analytics, automate repeatable workflows, identify patterns, and translate complex data into actionable commercial recommendations.
• Strong communication and storytelling skills, including presenting insights and recommendations to cross-functional partners and senior leaders and demonstrating the ability to align and influence.
• Strong understanding of data quality, data validation, data cleansing, root cause analysis, and issue resolution.
• Experience creating documentation, training materials, or adoption routines that help users understand and apply analytics solutions.

Nice To Haves

• Experience in consumer-packaged goods, retail, shopper insights, category management, space planning, revenue growth management, or commercial analytics.
• Experience working with customer, store, product, shopper, loyalty, point-of-sale, or retailer data.
• Experience using adoption metrics, stakeholder feedback, and business impact measures to improve analytics solutions over time.
• Experience with forecasting, segmentation, optimization, personalization, store targeting, or other advanced analytics methods.
• Familiarity with agile ways of working, including requirements gathering, backlog prioritization, Jira, GitHub, or similar tools.
• Experience mentoring analysts, guiding cross-functional partners, or leading work through influence.
• Commercial curiosity, analytical rigor, technical fluency, a product mindset, and the ability to turn complex information into practical growth actions.

Responsibilities

• Develop scalable shopper and commercial analytics to identify growth opportunities, improve retail execution, and turn complex data into actionable recommendations for assortment, space planning, segmentation, shopper activation, personalization, and commercial planning.
• Shape the roadmap and continuous improvement of Store DNA (sDNA) and related tools based on user needs, business priorities, adoption, impact, and technical feasibility.
• Partner with insights, sales, strategy, commercial planning, product, data engineering, and software engineering teams to define analytical solutions and delivery plans, leading through influence.
• Ensure analytical quality through data validation, business rules, issue resolution, and fit-for-purpose outputs while advancing analytical rigor and business translation.
• Develop results presentations, training, documentation, and enablement materials for technical and non-technical audiences.
• Track and improve business value through adoption, speed to insight, data quality, user satisfaction, use-case deployment, and application.

Benefits

• Performance-based annual bonus with a 12% target payout, subject to eligibility.
• Paid time off subject to eligibility, including paid parental leave, vacation, sick, and bereavement leave.
• Medical, dental, and vision benefits, subject to elections and eligibility.
• Disability benefits.
• Health and dependent care reimbursement accounts.
• Employee Assistance Program (EAP).
• Accident, group legal, and life insurance.
• Defined Contribution Retirement Plan.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager