- Descriptive Analytics: Analyzed historical data (stock, sales, campaign, brands) to evaluate and explain campaign performance- Queried available data, visualized results, and validated or rejected hypotheses using Python and SQL.- Created data pipelines using Python to automate the extraction of data from multiple sources (Google Sheets, Redshift, BigQuery, etc), enriched and restructured the data, and loaded it into tables- Engaged stakeholders to understand requirements and context for data extraction and developed subsequent reports on Tableau with desired aggregations- Developed and maintained Tableau dashboards to support day-to-day operations, and decision-making for various stakeholders- Supported the generation of half-yearly reporting by using advanced formulas in Google Sheets**Project: Improving the Brands Relevance Scoring Model**Problem: The previous model generated brand relevance scores that did not reflect the real presence of the brand in many markets. The model ranked the brands using globally aggregated data, which gave incorrect values for brands that had high popularity in select markets and lower popularity in other markets.Solution: The model was modified to generate a country-wise ranking of brands on the basis of their past sales performance in the Zalando Fashion Store, the volume of product page (PDP) clicks from the web analytics metrics on the Lounge website, and the popularity of the brand on the basis of Google Search (search volume metrics). These metrics were weighted on the basis of the brand clusters to generate the final relevance score. In further iterations, as an allowance for new or prospective Lounge brands, the model was updated to only consider the product page clicks of brands that had been a part of active campaigns and generated a sales volume above 1M in the past 2 years. This stopped the relevance score from being largely affected by low PDP clicks for such brands.

Markets & Sales Analytics in Zalando Lounge

Responsible for the modification of the open-source application (ARSnova) as per requirements provided by the university and subsequent deployment on the university infrastructure

Worked in the department of HSBC Private Bank, Switzerland- Designed and implemented new features in multiple applications using Java, SQL, and Web tech like JavaScript, XML, etc- Planned and designed the structure of technology systems for new requirements from the Business- Led the initiative for the adoption of CI/CD (Jenkins, Ansible, etc)- Performed drills for disaster recovery for production infrastructure- Minimized misinterpretations and stakeholder interference through efficient updates and clear communication- Mentored and trained new team members regarding team projects