Manager, Customer Analytics and Decision Science
PepsiCo · Plano, Chicago, Purchase · $110,700–$185,250 (stated in the posting)
OverviewThe North America Insights & Intelligence (NAI&I) Team
The North America Insights & Intelligence (NAI&I) team drive a human-centric and integrated Power of One (PO1) approach to insights and intelligence across our North America Commercial and Consumer organizations, to drive market-leading growth for PepsiCo. The team provides deep Food & Beverage expertise across Shopper Analytics & Insights, Consumer Insights, Commercial Intelligence and Category Leadership to build best-in-class capabilities and offer focused programs to drive growth with our customers.
What’s in it for you?
Join us to turn advanced analytics, decision science and shopper intelligence into solutions that shape retail strategies, strengthen marketplace execution, and accelerate growth across PepsiCo’s portfolio. In this role, your work will help PepsiCo and its retail partners make smarter, faster, and more impactful commercial decisions.
As a member of the Data and Analytics team, you will lead workstreams that make retail and marketplace insights actionable across the entire PepsiCo portfolio. You will develop strategies, introduce innovative analytical processes, and deliver insights that influence internal PepsiCo teams and major retailers throughout the United States. This is an opportunity to deepen your expertise in commercial and shopper intelligence while becoming a trusted advisor who translates business needs into technical requirements and delivers actionable insights that create measurable value.
What’s your role?
As Customer Analytics and Decision Science Manager you will help shape how PepsiCo uses data to understand shoppers, improve retail execution, and unlock growth across a broad portfolio of iconic brands. This role is ideal for someone who can connect commercial strategy, advanced analytics, and decision science insights. Turn shopper, store, product, and customer data into scalable insights and tools that guide assortment, space planning, segmentation, and go-to-market decisions. Partner across business, analytics, product, data, and engineering teams to deliver trusted solutions with measurable impact.
Responsibilities
- Develop scalable shopper and commercial analytics that 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.
Compensation and Benefits:
- The expected compensation range for this position is between $110,700 - $185,250.
- Location confirmed job-related skills, experience, and education will be considered in setting actual starting salary. Your recruiter can share more about the specific salary range during the hiring process.
- Bonus based on performance and eligibility target payout is 12% of annual salary paid out annually.
- Paid time off subject to eligibility, including paid parental leave, vacation, sick, and bereavement.
- In addition to salary, PepsiCo offers a comprehensive benefits package to support our employees and their families, subject to elections and eligibility: Medical, Dental, Vision, Disability, Health, and Dependent Care Reimbursement Accounts, Employee Assistance Program (EAP), Insurance (Accident, Group Legal, Life), Defined Contribution Retirement Plan.
Qualifications
- Bachelor’s degree in data science, Computer Science, Statistics, Business Analytics, Marketing Analytics, Economics, or a related field required
- Minimum of 5+ years of experience in analytics, commercial analytics, data/decision science, business intelligence, data product delivery, or a related field required
- Expert level SQL skills, with experience extracting, joining, aggregating, validating, and troubleshooting data from large and small data sets required
- 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, with experience presenting insights and recommendations to cross-functional partners and senior leaders with 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
Preferred Skills:
- Successful candidates will bring a mix of commercial curiosity, analytical rigor, technical fluency, product mindset, and the ability to turn complex information into practical growth actions.
- 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
EEO Statement
Our Company will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the Fair Credit Reporting Act, and all other applicable laws, including but not limited to, San Francisco Police Code Sections 4901-4919, commonly referred to as the San Francisco Fair Chance Ordinance; and Chapter XVII, Article 9 of the Los Angeles Municipal Code, commonly referred to as the Fair Chance Initiative for Hiring Ordinance.
All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status.
PepsiCo is an Equal Opportunity Employer: Female / Minority / Disability / Protected Veteran / Sexual Orientation / Gender Identity / Age
If you'd like more information about your EEO rights as an applicant under the law, please download the available EEO is the Law & EEO is the Law Supplement documents. View PepsiCo EEO Policy.
Please view our Pay Transparency Statement.
- Develop scalable shopper and commercial analytics that 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.
Compensation and Benefits:
- The expected compensation range for this position is between $110,700 - $185,250.
- Location confirmed job-related skills, experience, and education will be considered in setting actual starting salary. Your recruiter can share more about the specific salary range during the hiring process.
- Bonus based on performance and eligibility target payout is 12% of annual salary paid out annually.
- Paid time off subject to eligibility, including paid parental leave, vacation, sick, and bereavement.
- In addition to salary, PepsiCo offers a comprehensive benefits package to support our employees and their families, subject to elections and eligibility: Medical, Dental, Vision, Disability, Health, and Dependent Care Reimbursement Accounts, Employee Assistance Program (EAP), Insurance (Accident, Group Legal, Life), Defined Contribution Retirement Plan.
- Bachelor’s degree in data science, Computer Science, Statistics, Business Analytics, Marketing Analytics, Economics, or a related field required
- Minimum of 5+ years of experience in analytics, commercial analytics, data/decision science, business intelligence, data product delivery, or a related field required
- Expert level SQL skills, with experience extracting, joining, aggregating, validating, and troubleshooting data from large and small data sets required
- 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, with experience presenting insights and recommendations to cross-functional partners and senior leaders with 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
Preferred Skills:
- Successful candidates will bring a mix of commercial curiosity, analytical rigor, technical fluency, product mindset, and the ability to turn complex information into practical growth actions.
- 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