Gowtham Saravanan
Belfast
Summary
Data-driven professional with strong experience in reporting, analytics, and commercial insight generation. Skilled at simplifying complex data into actionable recommendations that drive business performance. Background in compliance, forecasting, and sales analysis with proven success in delivering data-led strategies to improve efficiency and customer experience. Currently pursuing an MSc in Business Analytics, with advanced expertise in statistical modelling, forecasting, and data visualization.
Overview
2
2
years of professional experience
Work History
Product Compliance Associate
Amazon
06.2021 - 03.2023
- Produced high-quality reporting and analysis to ensure compliance across multiple global marketplaces, enabling seamless operations.
- Delivered insights from large datasets, helping streamline classification processes and improve compliance accuracy.
- Partnered with cross-functional teams (operations, legal, and product) to drive efficiency and resolve compliance risks.
- Recommended process improvements that reduced operational bottlenecks and enhanced customer experience.
- Led stakeholder communications, providing clear reporting on compliance issues and progress updates to management.
Education
MSC - Business Analytics
Queen's University
Belfast, Northern Ireland10.2024
BE - Mechanical Engineering
SVS College of Engineering
05.2020
Skills
- Analytics & Insight: Data Visualization, Forecasting, Predictive Modelling, Reporting & Dashboarding
- Technical Skills: SQL (complex queries), Python, Tableau, Matplotlib, Machine Learning, GCP (familiarity), Qlik (familiarity)
- Business & Commercial Skills: Stakeholder Management, Business Case Development, Strategic Insight, Commercial Planning
- Professional Skills: Project Management, Critical Thinking, Problem Solving, Cross-Functional Collaboration
Timeline
Product Compliance Associate
Amazon
06.2021 - 03.2023
BE - Mechanical Engineering
SVS College of Engineering
MSC - Business Analytics
Queen's University
Projects
Walmart Sales Forecasting (MSc Dissertation)
- Designed machine learning models (Linear Regression, Random Forest, XGBoost) to forecast weekly sales across multiple store departments.
- Conducted extensive feature engineering, data preprocessing, and hyperparameter optimization to boost accuracy.
- Used Tableau and Matplotlib to visualize insights, presenting forecasts to support strategic decision-making.
- Delivered recommendations for improved inventory planning and sales performance.
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