• Responsible for identifying & implementing cost optimization opportunities for a large SaaS client looking to reduce the cost of their current AWS & GCP estate • Led implementation of cost optimization initiatives that involves liaising cross functionally with finance, engineering and internal FinOps functions, while escalating to CPO/CTO as required - saved client $11.2m annualized • Worked to reduce Kubernetes spend by $1.8m annualized by setting up a program to systematically flag teams with massive unused requests, aiding in reduction of number of clusters/nodes running in the estate – this involved building a cost allocation model at the container level, combining Datadog and AWS CUR data • Built a program to account for volatility in teams requests/usage to flag teams/containers ideal for HPA, with an aim to reduce wasted resources during downtime • Optimized BigQuery spend by segmenting workloads to better use latest pricing structures leading to an annualized reduction of $1.2m in spend • Additionally saved $2m-$3m annualized through leading several smaller initiatives such as through optimal savings plan coverage, utilizing DynamoDB provisioning & shifting to RDS IO instances • Worked with 4 other private equity clients to address their cloud estate problems regarding spend visibility, improved discounting and infrastructure tagging across their portfolio companies – built and maintained a tableau-based tool that addresses these problems specifically for their Google Cloud spend • Implementing and maintaining our cloud analytics offering (specifically for Google Cloud Platform) for 4 clients, bringing in a revenue of ~$1.2m through annual license fees • Built a COGS tool using Tableau and Python for one of our clients to help them understand their true storage, database and compute cost per tenant to breakdown their cost per region for multicloud spend – this is being used to charge back clients with high demo costs

• Back-office support from the R&D area to ongoing projects in analysing, summarising and distributing requirements on IRB models and Data Quality.• Review of TRIM guidelines and related applicable regulation (CRR, EBA RTS and ITS).• Review of BCBS 239 regulation and its application to financial institutions.

Elected by my classmates as a course representative on the Student Staff Liaison Committee to bridge the gap between them and the departmental staff by acting as a focal point for all their views and conveying them to the staff.

• Built a customer retention model for a client, predicting which customers would potentially return to a hotel.• Devoted 3 weeks to honing necessary skills for development of model on SAS and Excel.• Applied analytical skills to understand and analyse a live dataset for final model.• Initiated meetings with project manager to understand the underlying statistical and marketing strategies used to improve the businesses of clients.• Preparing and delivering weekly presentations to CRM team for approval and validation greatly enhanced my organisational skills.• Worked with members of CRM to understand the needs of various businesses and how CRM aids them.

• Reviewed the transfer of scrap cells worth ₹10 million for an industrial manufacturing client.• Conducted regular mediation sessions between the client and the vendor to ensure all operations (such as transfer of funds, logistics of movement of scrap cells, etc) ran smoothly.• Learned and applied EY’s methodology to carefully examine warehouse procedures thereby preventing fraudulent activities.• As this project required working with the warehouse workers, the vendor and the client, the analytics team chose me to represent EY due to my strong interpersonal skills.• Collaborated with my project manager to research the various financial/operational risks of an e-commerce client.