Job Description 

The Smart Business Data Analyst bridges the gap between business needs and data-driven solutions. This role involves analyzing data, identifying trends, and providing actionable insights to guide decision-making processes, improve business outcomes, optimize business strategies, improve customer experience, and enhance profitability. 

Key Responsibilities: 

Data Analysis and Interpretation 

• Gather, clean, and analyze large datasets to identify trends and insights. 
• Use statistical techniques to interpret data and generate business insights. 
• Deliver insights on potential areas of growth, optimization, and improvements. 
• Build models to forecast future trends or outcomes (e.g., sales, customer behavior). 

Budget Allocation & Forecasting 

• Assist in creating and monitoring budgets, ensuring alignment with business objectives. 
• Develop forecasting models for sales, costs, and campaign outcomes to guide decision-making. 

Performance Monitoring 

• Track key performance indicators (KPIs) to evaluate business success. 
• Monitor market trends and competitor data to provide strategic insights. 

Data Governance 

• Ensure data accuracy, integrity, and compliance with company and industry standards. 

Customer Journey & Basket Analysis 

• Map and analyze the customer journey to identify pain points and improvement opportunities. 
• Perform basket analysis to understand purchase patterns, product affinities, and cross-sell opportunities. 

Reporting & Stakeholder Collaboration 

• Create detailed and visually engaging dashboards and reports for stakeholders. 
• Work closely with stakeholders to understand business requirements and challenges. 
• Translate business needs into data models, analysis, and actionable recommendations. 
• Create real-time and ad-hoc reports to address specific business queries. 
• Present findings and recommendations to management and stakeholders. 

Skills & Qualifications: 

Essential: 

• Strong analytical skills with proficiency in data visualization tools (e.g., Power BI, Meta base) 
• Expertise in SQL, Excel, and statistical analysis tools (e.g., Python, R). 
• Solid understanding of business metrics (e.g., AOV, NMV, Gross Margin, CR). 
• Excellent communication and presentation skills. 

Preferred: 

• Experience in retail, e-commerce, or FMCG sectors. 
• Familiarity with predictive modeling and machine learning techniques. 

Competencies: 

• Data-driven approach. 
• Attention to detail and problem-solving skills. 
• Strong time management and organizational skills. 
• Ability to work collaboratively in a fast-paced environment