FAQs
What is the primary focus of the Logistics Data Analyst role at PepsiCo?
The primary focus of the Logistics Data Analyst role is to drive data insights and automation for PepsiCo's freight brokerage business, develop actionable strategies, and improve operational efficiency related to the company's $2B annual transportation spend.
What tools should I be familiar with for this position?
Candidates should be proficient in data tools such as Python, SQL, Power BI, and Tableau for building dashboards and reports.
What level of experience is required for this position?
The role requires 6 months to 2 years of relevant professional experience, or relevant internship or project experience.
Where is this position located?
This position is based in Plano, TX, at the PepsiCo headquarters.
Are there growth opportunities in this role?
Yes, the role offers a strong willingness to learn and grow in a dynamic business environment, as well as opportunities to develop problem-solving skills and collaborate with diverse teams.
What kind of compensation and benefits can I expect?
The expected compensation range for this position is between $64,300 - $107,650, along with a comprehensive benefits package that includes medical, dental, vision, paid time off, and retirement plans.
Is a specific degree required for the Logistics Data Analyst position?
Yes, a bachelor's degree in Data Analytics, Business, Computer Science, Engineering, or a related field is required.
Will I be working with internal teams in this role?
Yes, collaboration with internal teams is a key responsibility to understand data needs and deliver innovative solutions.
What is PepsiCo's stance on diversity and equal opportunity?
PepsiCo is an Equal Opportunity Employer and is committed to considering qualified applicants without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status.
What kind of work will I be doing on a daily basis?
Daily tasks will include analyzing large data sets, building dashboards and reports, supporting logistics operations with actionable analytics, and collaborating with teams to identify and implement data-driven solutions.