Job Title: Retail Data Analyst – Junior Level
Job Type: Full-Time
The Junior Retail Data Analyst is responsible for gathering, analyzing, and interpreting retail data to support business strategies and decision-making. This role involves working with sales, inventory, and customer behavior data to identify trends, optimize pricing, and enhance operational efficiency. The ideal candidate will have foundational experience in data analytics, proficiency in analytical tools, and a passion for using data to drive business growth.
Collect, clean, and analyze retail data from multiple sources, including sales reports, inventory systems, and customer transactions.
Identify patterns, trends, and insights to support pricing, sales, and marketing strategies.
Support demand forecasting and inventory management by analyzing historical sales data.
Assist in performance tracking of key retail metrics, including revenue growth, customer retention, and product performance.
Develop dashboards and reports using Excel, Power BI, Tableau, or other visualization tools.
Present data insights through clear visualizations and summaries for senior analysts and management.
Ensure data accuracy and consistency in reporting processes.
Conduct analysis to measure the effectiveness of promotions, discounts, and marketing campaigns.
Help optimize inventory levels by providing insights into demand fluctuations and stock performance.
Analyze customer purchasing behavior to assist in targeted marketing and segmentation efforts.
Work with data engineering teams to improve data collection, storage, and retrieval processes.
Assist in writing SQL queries and using Python or R for data extraction and deeper analysis.
Stay up to date on new trends and technologies in retail data analytics.
Bachelor’s degree in Statistics, Business Analytics, Data Science, Economics, or a related field.
1-3 years of experience in data analytics, preferably in a retail or e-commerce environment.
Proficiency in Excel, SQL, and data visualization tools like Power BI or Tableau.
Strong analytical and problem-solving skills, with a keen eye for detail.
Ability to interpret complex data sets and communicate insights effectively.
Basic knowledge of Python or R for data analysis is a plus.
Strong teamwork and communication skills.