📌 Job Description

1. Data Analysis & Technical Skills

🔹 Data Processing & Analysis

Analyze large volumes of retail-related data using Databricks and other tools.

Build and manage data pipelines and workflows in Databricks to streamline data processing and reporting for key retail metrics.

Apply advanced statistical techniques, machine learning models, and predictive analytics to derive actionable insights from retail data.

Experience with SQL, Python, or Scala for data manipulation and analysis.

Work with cloud platforms (Azure, AWS, Google Cloud) to build scalable solutions.

🔹 Business Intelligence Tools & Dashboards

Build interactive dashboards and reports in Databricks and other BI tools (e.g., Power BI, Tableau).

Ensure real-time visibility and data-driven decision-making for business leaders.

Proactively monitor data quality and ensure the accuracy of insights delivered to stakeholders.

🔹 Advanced Analytics & Reporting

Perform data analysis to support key retail metrics such as sales, inventory, pricing, promotions, and customer behavior.

Develop and deploy advanced analytics solutions for customer segmentation, sales forecasting, and inventory optimization.

🔹 Industry Knowledge

Deep understanding of retail-specific metrics and KPIs (e.g., sales performance, customer churn, stock levels, pricing optimization).

Expertise in retail operations, including the ability to translate retail challenges into actionable data-driven solutions.

Understanding of e-commerce, in-store, and omni-channel retail strategies.

🔹 Business Requirements & Problem Solving

Work closely with business stakeholders to gather requirements and provide actionable insights that improve business performance.

Identify trends and patterns in retail data, offering actionable recommendations to improve operational efficiency and customer experience.

3. Business Analysis & Stakeholder Collaboration

🔹 Business Analysis Skills

Engage with business stakeholders to define analytical solutions aligned with their goals.

Ability to communicate complex technical concepts to non-technical stakeholders.

Translate business needs into data requirements and actionable insights.

🔹 Cross-Functional Collaboration

Collaborate with data engineers, data scientists, and business leaders to drive data-driven strategies and decisions.

Provide mentorship and guidance to junior analysts and foster a collaborative team environment.

4. Communication & Presentation Skills

🔹 Reporting & Presenting Insights

Present data-driven insights and business recommendations in a clear, concise, and actionable manner to executive teams.

Develop reports that inform business strategies and facilitate decision-making at all levels.

🔹 Stakeholder Communication

Strong ability to understand stakeholder needs and provide timely updates on data analysis projects.

Clearly articulate data findings to business leaders, providing insights that impact business strategy.

5. Qualifications & Experience

🎓 Education

Bachelor’s or Master’s degree in Data Science, Business Analytics, Computer Science, Mathematics, or a related field.

💼 Experience

5+ years of experience in data analysis within the retail industry.

Strong experience with Databricks and related big data tools.

Proficiency with SQL, Python, or Scala for data manipulation and analysis.

Advanced knowledge of BI tools such as Power BI or Tableau.

Experience in forecasting, statistical modeling, and machine learning.

Experience working with cloud platforms (Azure, AWS, Google Cloud) is a plus.