Manager, Customer Analytics and Decision Science
About The Position
The Manager, Customer Analytics and Decision Science is part of PepsiCo’s North America Insights & Intelligence team and Data and Analytics team. The role makes retail and marketplace insights actionable across PepsiCo’s portfolio, helping PepsiCo and retail partners make informed commercial decisions. It combines commercial strategy, advanced analytics, shopper intelligence, and decision science to improve retail execution and unlock growth. The manager turns shopper, store, product, and customer data into scalable insights and tools for assortment, space planning, segmentation, shopper activation, personalization, and go-to-market decisions. The role leads workstreams and partners with business, analytics, product, data, and engineering teams to deliver trusted analytical solutions with measurable business impact. It also shapes the roadmap and continuous improvement of Store DNA (sDNA) and related tools, while translating business needs into technical requirements and practical recommendations.
Requirements
- Bachelor’s degree in data science, computer science, statistics, business analytics, marketing analytics, economics, or a related field.
- Minimum of 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 demonstrated 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 ability to turn complex information into practical growth actions.
Responsibilities
- Develop scalable shopper and commercial analytics to identify growth opportunities, improve retail execution, and make complex data actionable for assortment, space planning, segmentation, shopper activation, personalization, and commercial planning.
- Shape the roadmap and continuously improve 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 target payout of 12% of annual salary, subject to eligibility.
- Paid time off, subject to eligibility, including paid parental leave, vacation, sick, and bereavement leave.
- Medical, dental, vision, and disability benefits, subject to elections and eligibility.
- Health and dependent care reimbursement accounts, subject to elections and eligibility.
- Employee Assistance Program (EAP).
- Accident, group legal, and life insurance, subject to elections and eligibility.
- Defined Contribution Retirement Plan.
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What This Job Offers
Job Type
Full-time
Career Level
Manager
