Anderson Merchandisers
Retail Analytics & Insights Analyst
5601 Granite Pkwy Ste 1400, Plano, TX 75024-8601
Full-time
First seen by offpeak October 9, 2026
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WE ARE LOOKING FOR GREAT PEOPLE TO JOIN OUR TEAM- just like you!
Our associates have a lot in common. They have great interpersonal skills, enjoy working independently, are self-motivated, and have a relentless drive. Did we mention that while they are working hard, they also like to have fun?
We offer flexible hours, competitive pay, and great benefits for both full and part-time associates.
If this sounds like a good fit for you, come join our team!
As an Anderson Merchandisers Associate, you may be eligible for these benefits*.
• Flexible work schedules
• 401(k) retirement plan
• Health Insurance – including Dental and Vision
• Telehealth
• Health Savings Account
• Accident Insurance
• Critical Illness Insurance
• Life Insurance
• Long Term Care
• Short Term Disability
• Long Term Disability
• Associate Assistance Fund
• Anderson Cares Natural Disaster Fund
• Associate Savings Plan
• Anderson Cares Fund
• Paid Time Off
• Discounts - Cell Phone, Vehicle, Pet Insurance
• Training & Career Development
*All benefits subject to eligibility per company policy.
The Retail Analysis & Insights Analyst is responsible for data manipulation, analysis, and reporting to address business questions from clients or internal partners (including but not limited to Operations, Marketing, Client Services, Finance, Business Operations, and HR). The role involves translating analytical and reporting requirements into a clear data scope, building and executing SQL queries, and delivering user-friendly reports and data outputs. This position requires strong logical thinking, problem-solving skills, and proficiency in SQL.What would you do in this role?
Key Responsibilities
Build foundational knowledge of business processes, workflows, and performance drivers across assigned functional areas.
Develop a deep understanding of available data sources, data structures, definitions, and quality considerations.
Partner with stakeholders to understand the “why” behind business questions and reporting needs.
Create, modify, and maintain SQL queries to support standard reporting, ad-hoc analysis, and operational needs, primarily using data warehouse tables and occasionally external data sources.
Build and maintain dashboards that clearly communicate KPIs, trends, and insights to technical and non-technical audiences.
Translate analytical findings into clear, actionable summaries and recommendations.
Map current-state workflows and reporting processes to identify inefficiencies, data gaps, or improvement opportunities.
Identify patterns and trends in data that suggest opportunities for process improvement, automation, or enhanced decision-making.
Support implementation of incremental improvements in reporting, analytics workflows, or data usage.
Collaborate closely with Technology teams and other Analytics team members to extract, validate, and document accurate datasets.
Communicate analytical requirements, data limitations, and findings clearly to stakeholders with varying levels of technical expertise.
Manage assigned workstreams day-to-day, ensuring clarity on scope, timelines, and business impact.
Other Duties - Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.
Skills & Qualifications Required
Strong logical thinking and problem-solving skills.
High attention to detail with a focus on data accuracy and quality.
Ability to gather, document, and validate business requirements with guidance.
Positive, collaborative mindset with a focus on continuous improvement.
Proactive learner who seeks to build both technical and business acumen.
Self-starter who can prioritize tasks and learn quickly in a dynamic environment.
Education & Experience Required
Bachelor’s degree in Data Analytics, Computer Science, Mathematics, Statistics, Engineering, or another quantitative discipline.
Experience in data manipulation using SQL with large-scale data repositories.
Experience in BI tools such as Tableau, Qlik, PowerBI, Sigma, or similar platforms.
Exposure to or familiarity with Python for data analysis, data preparation, or exploratory analysis is a plus, but not required.
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