Data Analyst

1. Data Analysis & Reporting

• Collect, clean, and consolidate stock audit data from multiple systems (POS, inventory system, and audit reports).
• Develop dashboards and regular reports showing key metrics such as shrinkage %, top loss SKUs, and high-risk stores.
• Perform variance analysis between system stock vs. physical count to detect irregularities and highlight areas of concern.
• Identify trends and patterns related to store operations, product categories, or audit results.

2. Strategic Insight & Stakeholder Linkage

• Understand the business context behind data — how stock variance impacts finance, operations, and fraud prevention.
• Translate analytical results into strategic insights that help stakeholders make decisions (e.g., Area Managers, Operations, Finance, and Loss Prevention teams).
• Map data relationships between systems and functions (sales, purchasing, stock transfer, promotion, write-off) to ensure holistic analysis.
• Provide data-based recommendations that align with company loss reduction goals (e.g., reduce stock loss to 0.2% of sales).
• Anticipate how findings can influence policy, store SOPs, and audit focus.

3. Root Cause Investigation

• Collaborate with audit and store teams to identify root causes of discrepancies (process gaps, theft, system errors).
• Support fraud investigations with data evidence such as transaction trails, timestamps, and behavior patterns.
• Apply analytical techniques (correlation, trend analysis, anomaly detection) to uncover hidden causes.

4. Dashboard & Data Visualization

• Design and maintain Power BI/Tableau/LookerStudio dashboards to monitor stock loss, count accuracy, and high-risk stores.
• Automate recurring reports and build exception alerts for unusual stock variance or suspicious transactions.
• Present insights through visuals and summaries that are actionable for non-technical audiences.

5. Process Improvement & Business Impact

• Recommend improvements to stock audit procedures and store controls based on data findings.
• Track the results of corrective actions and quantify impact on loss reduction.
• Contribute to the development of data-driven SOPs for stock counting and reconciliation.

6. Collaboration & Communication

• Work closely with IT/Data teams to improve data structure and data flow.
• Partner with Finance, Operations, and Loss Prevention teams to ensure consistent interpretation of data and KPIs.
• Communicate findings clearly to management through reports and presentations that link data insights to business strategies.

Qualifications:

• Bachelor's degree in Statistics, Data Science, Business Analytics, Accounting, or related field.
• 2–4 years of experience in data analysis, preferably in retail, audit, or inventory management.
• Strong analytical and problem-solving skills with a strategic mindset.
• Proficiency in Excel, visualization tools (Power BI, Tableau), SQL (preferable)
• Understanding of data relationships across retail processes (sales, inventory, transfer, shrinkage).
• Ability to translate data into actionable insights for multiple stakeholders.
• Strong communication and storytelling skills.