Job Title: Retail Data Analyst – Mid-Level
Job Type: Full-Time
The Mid-Level Retail Data Analyst is responsible for analyzing large datasets to generate insights that drive business decisions in retail operations, sales, and customer engagement. This role involves developing advanced reporting, forecasting sales trends, optimizing inventory, and working closely with cross-functional teams to enhance data-driven decision-making. The ideal candidate will have experience in data analytics, proficiency in statistical modeling, and a strong ability to translate data into actionable strategies.
Collect, clean, and analyze retail data from multiple sources, including sales reports, CRM systems, and market research.
Identify trends, patterns, and correlations in customer behavior, pricing strategies, and product performance.
Develop predictive models to support demand forecasting, pricing optimization, and customer segmentation.
Provide actionable insights to optimize sales, inventory, and merchandising strategies.
Design and maintain interactive dashboards and reports using Power BI, Tableau, or similar tools.
Present data findings to stakeholders through visual storytelling and detailed analysis.
Ensure data accuracy, consistency, and integrity across various reporting systems.
Analyze the effectiveness of promotions, discounts, and marketing campaigns to improve ROI.
Work with supply chain and inventory teams to ensure optimal stock levels based on sales trends and seasonality.
Support pricing teams in competitive analysis and margin optimization strategies.
Work with IT and data engineering teams to automate data collection and reporting processes.
Utilize SQL, Python, or R to perform complex data extractions and deep-dive analysis.
Recommend improvements in data collection methods and analytics tools to enhance efficiency.
Stay informed on industry trends and emerging technologies in retail analytics.
Bachelor’s degree in Data Science, Business Analytics, Statistics, Economics, or a related field.
3-5 years of experience in data analytics, preferably within the retail or e-commerce industry.
Proficiency in SQL, Excel, and data visualization tools like Power BI or Tableau.
Strong analytical and problem-solving skills with a data-driven mindset.
Experience with statistical modeling, machine learning, or predictive analytics is a plus.
Excellent communication skills, with the ability to present complex data to non-technical stakeholders.
Ability to manage multiple projects and work in a fast-paced environment.