Retail Operations Data Analyst

The Rundown AI, Inc.; Seattle (WA); On-site; USD 85,000 - 110,000; Full time

Job summary

A leading company is seeking a Retail Operations Data Analyst to manage data visualization and operations for Reality Labs products. The role involves building processes, managing data, and collaborating across teams to enhance retail operations and customer experiences. Candidates should have extensive experience in data management and visualization tools like Tableau, with a strong focus on accuracy and communication.

Qualifications

• 5+ years of experience in designing, building, and managing data visualizations.
• Experience managing data pipelines and ingestion processes.

Responsibilities

• Build processes for the retail organization based on business needs.
• Manage, maintain, and visualize large volumes of data using Tableau.
• Develop and launch KPI management tools and dashboards.

Skills

Data Visualization

Communication

Attention to Detail

Education

Bachelor’s degree in Business

Bachelor’s degree in Economics

Bachelor’s degree in Statistics

Bachelor’s degree in Data Science

Tools

Tableau

PowerBi

Alteryx

Hive

SQL

Job description

Meta is seeking a Reality Labs (RL) Retail Operations Data Analyst. This role involves planning, budgeting, communicating, building, maintaining, and reporting on all aspects related to Channel Enablement Operations programs across existing and future partners. A retail operations focus is essential for this position, which aims to help customers find, learn, and experience Reality Labs products through physical retail stores.

The primary responsibility of the RL Retail Operations Data Analyst is to manage data with accuracy, accessibility, and visualization in mind. The role emphasizes impact, accuracy, and organization, with the goal of defining effective processes. Candidates should have experience in fast-paced environments, managing multiple projects collaboratively, and communicating clearly across teams.

Retail Operations Data Analyst Responsibilities:

1. Build processes for the retail organization based on business needs and requirements.
2. Manage, maintain, and visualize large volumes of data from multiple sources globally using Tableau.
3. Partner with Channel Marketing Managers, Strategic Account Managers, 3rd party labor partners, Analytics, and Channel Services teams to ensure efficient and accurate business operations.
4. Act as a liaison between global 3rd party labor partners, channel marketing managers, and channel services for data management.
5. Make calculated decisions to maximize ROI and efficiency by leveraging partnerships with the analytics team.
6. Create detailed analysis recommendations for various Reality Labs initiatives across product lines.
7. Establish, maintain, and enforce in-store data collection processes with 3rd party labor partners.
8. Review instructions and project execution with attention to detail.
9. Manage field execution reporting via dashboards for internal stakeholders.
10. Develop and launch KPI management tools and dashboards, coordinating with engineering resources.

Minimum Qualifications:

• 5+ years of experience in designing, building, and managing data visualizations.
• Proficiency with Tableau, PowerBi, Alteryx, Hive, and other visualization tools.
• Experience managing data pipelines and ingestion processes.
• Understanding of retail operations and their impact on planning and initiatives.
• Experience communicating project updates across teams.
• High accuracy and attention to detail in reporting.
• Experience managing relationships with stakeholders and vendors.
• Bachelor’s degree in Business, Economics, Statistics, Data Science, or related field.

Preferred Qualifications:

• Experience in consumer electronics.
• Expertise in Microsoft and Google Suite.
• Familiarity with retail partner guidelines and processes.
• Experience managing analysis and budgets for brands.
• Experience reporting on large launches and programs.
• Ability to work in highly cross-functional teams.
• Skill in translating complex data and engineering concepts for broad audiences.
• Experience with AI-enhanced data modeling and analysis.
• Knowledge of SQL, including subqueries, joins, window functions, etc.