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Shopper Insights Sr. Analyst- New York
Shopper Insights Sr. Analyst- New York-April 2024
Purchase
Apr 21, 2025
ABOUT PEPSICO
Headquartered in Purchase, NY, PepsiCo is the global leader in food and beverages and operates in over 200 countries and territories around the world.
10,000+ employees
Consumer Goods & Services, Food & Beverage
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About Shopper Insights Sr. Analyst- New York

  Overview

  Candidate can sit in any of our HQ Locations: NY, IL, TX

  Main Purpose of the role:

  Are you excited about analytics? Passionate about problem solving? Ready for growth? Then come join the Demand Accelerator team in PepsiCo! We're a team that focuses on transformation of Shopper Insights, Shopper Marketing, Category Leadership, and Space Engineering resources to support Sales and Marketing plans for enterprise, national, and regional customers across the PepsiCo portfolio. This approach allows us to build best-in-class capabilities, develop deep functional expertise, and offer focused programs to drive growth with our customers. The Demand Accelerator team helps PepsiCo provide our customers with cutting edge data and insights as well as personalized solutions to drive incremental growth.

  Help us solve new and exciting questions with data science, advanced analytics, and a love of problem solving. As a member of the Data Science team you will help make shopper insights actionable across the entire PepsiCo portfolio. Your analysis will be used to create new strategies and apply new analytical processes that will be shared with internal PepsiCo teams as well as with major retailers all over the United States.

  Responsibilities

  As a Sr. Data Scientist, you will serve as a critical member of the Shopper Insights team impacting consumers and helping advance the thinking and capabilities of PepsiCo across all Business Units and many Business Functions. You will be collaborating in a matrixed environment, partnering with technical and business teams to deliver a variety of projects. As an integral part of the team, you would have the unique opportunity to work on and deliver advanced analytics and data science projects from end-to-end. These projects have far reaching impact across US Retailers and PepsiCo Brands.

  You will work across groups to prioritize needs, translate business needs to technical requirements, work with the internal teams to outline the specific data needs for each business analysis project, validate data integrity and solve for anomalies, arrive at an analytical solution and present your analysis. To do well in this role you need a very fine eye for detail, experience as a data scientist, and understanding of the popular data analysis tools and databases such as SQL, Python and Tableau.

  Act as contributor in innovation activities.Active contributor to code development in projects and services.Partner with data engineers to ensure data access for discovery and proper data is prepared for model consumption.Coordinate work activities with Business teams, other IT services and as required.Demonstrated experience in handling large data sets and relational databases.Communicate with business stakeholders in the process of service design, training and knowledge transfer.Support large-scale experimentation and build data-driven models.Refine requirements into modelling problems.Influence product teams through data-based recommendations.Research in state-of-the-art methodologies.Create documentation for learnings and knowledge transfer.Provide ad-hoc analysis and deliverables as requested

  Compensation & Benefits:

  The expected compensation range for this position is between $74,800 - $125,300. based on full-time schedule.Location confirmed job-related skills and experience will be considered in setting actual starting salary.Bonus based on performance and eligibility target payout is 8% 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

  Years of Experience, prior to the career break:

  2-3 Years' Experience in consumer brand/shopper marketing/innovation/insights

  Preferred Requirements:

  Bachelor's degree in Computer Science, Statistics, Information Systems or a related field with technical experience2 ~ 3+ years of experience with data scienceDemonstrated experience in handling large data sets and relational databasesMust know how to write SQL and extract/aggregate data from large and small databasesExperience with time series forecasting model and unsupervised machine learningExperience with Python, PySpark and SQLAbility to translate business and technical requirements into non-technical termsHigh-level written and verbal communication skillsProvide ad-hoc analysis and deliverables as requestedResults oriented with the ability to complete assignments in a timely mannerProviding technical expertise on data storage structures, data mining, and data cleansingPassionate about problem solving and continued learning in both technical skills as well as leadership skillsFamiliarity with statistical modeling, machine learning and/or deep learning modeling

  Percent Travel: 5-10%

  EEO Statement

  All qualified applicants will receive consideration for employment without regard to 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

  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

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