Description

Hi, I'm Priya Garg, a Data Analyst with over 4 years of experience across e-commerce, banking, and financial services. I specialize in SQL, Python, and BI reporting, with a strong background in pricing analytics, A/B testing, and data pipeline automation. Currently, I'm based in Zurich working with Luxoft on the UBS/Credit Suisse integration, focusing on compliance data workflows. Previously, I've worked with companies like Zepto, Meesho, and American Express, where I built dashboards, automated pipelines, and drove data-driven decisions. I'm now looking for opportunities where I can bring my analytics expertise to solve impactful business problems.

Languages

English
Native or bilingual

Workplace preferences

Remote only

Primarily works remotely

UBS
Technical Analyst
BANKING AND INSURANCE
October 2025 - Today (8 months)
Zürich, Switzerland
• • Automated end-to-end customer data preservation workflows for the Credit Suisse integration using SQL, significantly reducing manual effort and error rates.
• • Managed Legal Hold and compliance workflows, ensuring accurate and auditable preservation of sensitive financial data.
• • Validated and maintained large datasets using EMS and Microsoft Access, improving data quality and turnaround time.
SQL Microsoft Excel Data analysis AI Automation
Zepto (Quick Commerce, India)
Senior Product Analyst – Pricing & Strategy
November 2023 - January 2025 (1 year and 2 months)
• • Designed and evaluated dynamic pricing rules across product categories, directly contributing to margin target achievement.
• • Led A/B testing in fresh produce segments, increasing gross profit per order by ₹0.42 for key customer groups.
• • Built Databricks and Airflow pipelines powering real-time pricing dashboards and automated reporting.
Meesho (E-Commerce,
Business Analyst – Strategy & Operations
March 2022 - November 2023 (1 year and 8 months)
India
• • Defined success metrics and led experimentation for high-impact promotional events, driving measurable revenue uplift.
• • Performed RFM segmentation of metro customers, enabling targeted marketing campaigns and improving repeat purchase rates.
• • Analysed cancellation patterns and supported logistics shift to home delivery, reducing cancellations by 40%.