Senior Sales Analyst – Walmart Poultry

Tyson Foods, Inc.•Springdale, AR

2d•Onsite

About The Position

The Senior Sales Analyst for Walmart Poultry at Tyson Foods turns internal, customer, and market data into actionable insights to improve decision-making and drive growth across the Poultry portfolio. The role develops sales reporting and analytical tools, supports customer business management and execution, and partners across functions to deliver accurate reporting, stronger category performance, and effective implementation of business initiatives. The analyst evaluates sales and category performance using internal, Circana, and Scintilla data; provides regular performance updates and recommendations; and develops dashboards, scorecards, and other tools for customer business managers and commercial leadership. The role also works directly within Walmart systems, supports item setup and digital shelf audits, coordinates samples for customer initiatives, and helps deliver customer presentations, business reviews, and line reviews. It is office-based five days per week, with occasional after-hours availability required.

Requirements

Bachelor’s degree or relevant professional experience.
Ability to analyze large data sets, develop reporting tools, and convert findings into clear, customer-focused recommendations.
Strong analytical skills to interpret complex data, identify business drivers, and generate actionable insights.
Understanding of sales, volume, revenue, profitability, and customer execution across a complex product portfolio.
Ability to communicate complex insights clearly to leadership, cross-functional teams, and external partners, including Walmart.
Ability to collaborate across teams, influence stakeholders, and align actions with business priorities.
Ability to adapt and solve problems in a fast-paced, dynamic environment.
Willingness and ability to perform the physical requirements of the job, with or without reasonable accommodation.
Office-based role five days per week; occasional after-hours availability is required.

Nice To Haves

1–3 years of experience in sales analytics, category analysis, customer planning, business intelligence, or a related field.
CPG or food industry experience.
Experience working with customer POS data and syndicated data platforms such as Circana.
Experience with Walmart systems, including Scintilla, Item 360, and related reporting or eCommerce platforms.

Responsibilities

Analyze internal, Circana, and Scintilla data to identify performance trends, risks, and growth opportunities across categories, subcategories, brands, and SKUs.
Provide weekly and monthly performance updates to Sales and commercial leadership, with recommendations that support assortment, category growth, and commercial objectives.
Translate business challenges, questions, and user needs into analytical solutions and actionable recommendations.
Evaluate pricing, assortment, distribution, promotional activity, inventory, consumer behavior, and sales trends to explain performance and guide decisions.
Define data integration requirements and interface specifications for customer, third-party, and internal sources used in sales reporting and analytical systems.
Develop, maintain, and enhance dashboards, scorecards, and analytical tools for customer business managers and commercial leadership.
Drive adoption of sales analytics tools and understanding of key performance metrics that enable omni-channel growth.
Support line reviews, seasonal program recaps, customer presentations, internal business reviews, and ad hoc analysis, providing clear insights and recommendations.
Work directly within Walmart systems to support sales execution and day-to-day business management.
Manage item setup and audit digital shelf content through Item 360 and other eCommerce platforms.
Coordinate sample procurement and delivery for customer initiatives and sales team needs.
Partner with Sales, Supply Chain, Marketing, SS&P, and Customer teams to execute business initiatives.
Improve reporting processes and business routines through scalable solutions, automation, and best practices.
Establish consistent definitions, metrics, and standards to improve data quality, accuracy, and speed of decision-making.
Use approved AI tools responsibly, safeguard sensitive information, follow company policies, validate outputs, and apply professional judgment.