Senior Data Analyst; Retail

Senior Data Analyst (Retail) [206423]

Join to apply for the Senior Data Analyst (Retail) [206423] role at Aquent.

This range is provided by Aquent. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

$81.00/hr - $90.00/hr

Imagine contributing to a world‑renowned organization that shapes unparalleled consumer experiences across diverse global platforms. Our client, a globally recognized leader in entertainment and consumer experiences, is seeking a talented Senior Data Analyst to drive critical retail analytics initiatives. This is an exceptional opportunity to transform vast datasets into actionable insights that directly influence strategic decisions, enhance customer satisfaction, and optimize business performance across expansive retail operations, spanning both physical and digital storefronts.

As a key partner with Aquent, you will play a pivotal role in shaping the future of retail strategy through data‑driven innovation. In this dynamic role, you will be at the forefront of data exploration and insight generation. You’ll dive deep into retail performance metrics, develop intuitive dashboards, and collaborate with cross‑functional teams to translate complex data into clear, compelling narratives.

• Conduct in-depth analyses on retail performance, including pricing, promotional effectiveness, customer behavior, and product lifecycle, to inform strategic merchandising and planning decisions.
• Design, build, and maintain intuitive, automated dashboards and self‑service reporting tools using leading data visualization platforms to monitor key performance indicators and empower cross‑functional teams.
• Partner closely with merchandising, marketing, finance, and technology stakeholders to translate complex business challenges into data‑driven solutions and effectively communicate analytical findings.
• Develop robust and scalable analytical solutions by writing advanced SQL code to query, clean, and manipulate large datasets from cloud‑based sources, ensuring repeatable and efficient workflows.
• Collaborate with data scientists on advanced analytical projects, preparing essential data inputs, conducting exploratory data analysis, and validating model outputs for business relevance.

• Education & Experience:
  
  Bachelor’s degree in Mathematics, Economics, Data Analytics, Computer Science, or a related quantitative field, OR 4+ years of direct experience in a retail analytics or business intelligence role.
• Business Acumen: 4+ years of proven experience with a strong understanding of retail Key Performance Indicators (KPIs) and operations, demonstrating the ability to translate data into impactful business recommendations that drive revenue, efficiency, and customer satisfaction.
• Retail Analytics Expertise: 4+ years of experience supporting various business functions including merchandising, buying, planning, operations, and marketing within diverse retail environments, encompassing both physical and digital channels. Familiarity with retail inventory systems, point‑of‑sale (POS) data, and product lifecycle metrics is essential.
• Advanced SQL & Data Management: 4+ years of advanced SQL skills for extracting, joining, and transforming large datasets; hands‑on experience with leading cloud‑based data warehouses.
• Dashboarding & Data Visualization: 4+ years of expert‑level experience in building compelling dashboards and reports using leading data visualization tools to enable self‑service analytics and powerful business storytelling.

• Advanced Degree:
  Master’s or PhD in Mathematics, Economics, Data Science, Computer Science, Operations Research, or a closely related quantitative field.
• Python for Analytics: 3+ years of proficiency in Python for data analysis, utilizing libraries such as pandas, Num Py, and matplotlib, with the ability to support data preparation and light modeling tasks.
• Statistical Knowledge:
  Understanding of A/B testing concepts and fundamental statistical techniques.

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