Ranveer Panda

Results-driven Data Analyst with 2+ years of experience in retail pricing, promotional analytics, and business intelligence across the US retail and e-commerce sectors. Delivered actionable insights using SQL, Python, Power BI, and Databricks that directly supported revenue optimisation, promotional strategy, and executive decision-making. Proven ability to automate reporting workflows, build self-serve dashboards, and translate complex datasets into measurable business outcomes.

Enterprise Insights Analyst Apprentice at Giant Eagle GCC (2025-05 – Present)

Analysed pricing and promotional strategies across retail categories using SQL and Databricks to inform quarterly pricing decisions.

• Analysed pricing and promotional strategies across 10+ retail categories using SQL and Databricks, surfacing revenue optimisation opportunities that informed quarterly pricing decisions.
• Built 5 interactive Power BI dashboards integrating Dunnhumby, Numerator, and Circana datasets, reducing executive reporting preparation time by ~4 hours per week.
• Automated 3 recurring data extraction and transformation workflows using Python, eliminating ~6 hours of manual effort per reporting cycle.
• Generated TPR (Temporary Price Reduction) performance insights across 500+ SKUs, directly supporting the pricing team in identifying $200K+ in margin recovery opportunities.
• Engineered a Python web scraping pipeline to collect real-time competitor product pricing from Walmart, Kroger, and Meijer, enabling side-by-side price benchmarking that directly informed promotional pricing strategy.
• Collaborated with merchandising, finance, and marketing stakeholders to define 15+ KPIs, standardising reporting definitions across teams.

Market & Promotion Analyst Intern at Webifii (2024-11 – 2025-03)

Analysed marketing campaign data and conducted pricing benchmarking analysis to optimise ad spend and promotional strategies.

• Analysed marketing campaign data across 8 client accounts, identifying top-performing segments that improved average CTR by 18%.
• Evaluated KPIs including CTR, conversion rates, and cost-per-acquisition to optimise ad spend allocation, contributing to a 12% reduction in campaign waste.
• Conducted pricing and competitor benchmarking analysis across 3 product categories, delivering recommendations adopted in the next pricing cycle.
• Cleaned and transformed 50K+ row datasets in Excel, resolving data quality issues and improving reporting accuracy.
• Delivered bi-weekly stakeholder presentations translating campaign performance data into clear, actionable recommendations.

Data Analyst Intern at Conquest Techno Solutions (2024-04 – 2024-06)

Cleaned and analysed structured datasets to support monthly business reporting requirements using SQL and Excel.

• Cleaned and analysed structured datasets of 20K+ records using SQL and Excel to support monthly business reporting requirements.
• Performed data transformation pipelines using Python (Pandas, NumPy), improving data quality scores by 25% and reducing downstream reporting errors.
• Built 3 operational reports used by management for weekly performance tracking, cutting report generation time from 2 hours to 30 minutes.
• Designed and implemented data validation checks and automated quality controls, reducing data inconsistencies and improving overall reporting reliability.

Post Graduate Diploma in Business Intelligence Analysis – Mount Carmel College (2024 – 2025)

BSc in Physics and Electronics (Double Degree) – St. Joseph's University (2021 – 2024)