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The purpose of hiring this role is to establish dedicated ownership for the oneNA category forecast capability, which is critical to delivering unified, scalable, and accurate demand forecasts across North America markets.

The Data Science Associate Principal Scientist will:

• Own and operate the oneNA category forecasting engine across PBUS, PFUS, and future Quaker and Canada F&B markets.
• Modernize inherited forecasting methodologies and drive bestinclass model design. Develop, enhance, and deploy DS modules to support categorylevel demand forecast accuracy, consistency, and governance.
• Partner with demand planners and forecast analysts across business units to validate and refine outputs.
• Lead prioritization and delivery of product enhancements aligned with the oneNA roadmap.
• Lead a small team of data scientists, providing technical direction and coaching.

Compensation and Benefits:

• The expected compensation range for this position is between $93,500 - $156,450.
• 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 10% 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.

• Education: Bachelor in Data Science, Statistics, Operations Research, Computer Science, Engineering, Economics, or a related quantitative discipline is required.
• Master’s is preferred.
• Experience: 7+ years of experience in applied data science, advanced analytics, or forecasting, including ownership of endtoend analytical solutions in production environments.
• Demonstrated experience developing, deploying, and maintaining forecasting or predictive modeling solutions at scale.
• Technical Skills: Strong expertise in statistical modeling, timeseries forecasting, and machine learning, including model validation, accuracy/bias assessment, and performance diagnostics.
• Proficient in Python with a track record of writing productionquality, welldocumented, and reusable code.
• Experience working with cloudbased analytics platforms (e.g., Azure), including automated pipelines, model deployment, and runtime or cost optimization.
• Product Ownership: Proven ability to independently own complex analytical products, including lifecycle management, roadmap definition, and continuous improvement.
• Experience modernizing existing or fragmented methodologies and driving standardization, scalability, and governance.
• Business Partnership: Strong experience partnering with business stakeholders to validate analytical outputs and translate insights into decisions.
• Ability to clearly communicate complex analytical concepts to both technical and nontechnical audiences.
• Leadership: Experience providing technical leadership and mentorship to data scientists, including guidance on modeling approaches, code quality, and prioritization.
• Demonstrated ability to lead work across multiple stakeholders and initiatives concurrently.

Preferred Qualifications

• Experience with categorylevel, hierarchical, or longterm demand forecasting.
• Familiarity with scenario simulation and advanced forecast enhancement techniques.
• Experience supporting multimarket or multiregion analytical solutions in an enterprise setting.
• Prior experience working in globally distributed teams.

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. 

• Education: Bachelor in Data Science, Statistics, Operations Research, Computer Science, Engineering, Economics, or a related quantitative discipline is required.
• Master’s is preferred.
• Experience: 7+ years of experience in applied data science, advanced analytics, or forecasting, including ownership of endtoend analytical solutions in production environments.
• Demonstrated experience developing, deploying, and maintaining forecasting or predictive modeling solutions at scale.
• Technical Skills: Strong expertise in statistical modeling, timeseries forecasting, and machine learning, including model validation, accuracy/bias assessment, and performance diagnostics.
• Proficient in Python with a track record of writing productionquality, welldocumented, and reusable code.
• Experience working with cloudbased analytics platforms (e.g., Azure), including automated pipelines, model deployment, and runtime or cost optimization.
• Product Ownership: Proven ability to independently own complex analytical products, including lifecycle management, roadmap definition, and continuous improvement.
• Experience modernizing existing or fragmented methodologies and driving standardization, scalability, and governance.
• Business Partnership: Strong experience partnering with business stakeholders to validate analytical outputs and translate insights into decisions.
• Ability to clearly communicate complex analytical concepts to both technical and nontechnical audiences.
• Leadership: Experience providing technical leadership and mentorship to data scientists, including guidance on modeling approaches, code quality, and prioritization.
• Demonstrated ability to lead work across multiple stakeholders and initiatives concurrently.

Preferred Qualifications

• Experience with categorylevel, hierarchical, or longterm demand forecasting.
• Familiarity with scenario simulation and advanced forecast enhancement techniques.
• Experience supporting multimarket or multiregion analytical solutions in an enterprise setting.
• Prior experience working in globally distributed teams.