• Checking feasibility of certain methods/ideas as Proof of Concept (POC) projects with the help of supervised and unsupervised algorithms which can help Clients to identify new business opportunities• Identifying local brands which can be a potential threat to well established premium brands using K-Means clustering methods• Classifying the stores into RMS defined shop types based on the sales data obtained from POS systems using modern classification machine learning techniques

• Supported the Client Service team in investigating coverage related issues raised by global FMCG clients (P&G, Unilever, Coca Cola etc.) by performing in-depth analysis at Country/Category/Brand/SKU level• Responsible for preparing insightful decks / Graphs / Summary Excel Files / Word documents in a ready to present to Client format• Prepared VBA codes to automate some of the time consuming tasks to increase productivity• Owned a process which creates Market-at-a-Glance reports. These reports give an overview of Nielsen Retail Measurement Services (RMS) in a Country• Involved in a team which performs Country Tier classification. This classification helps Clients to make better decisions.

• Teaching statistical and Financial Mathematics related subjects such as Time Series Analysis, Probability Theory, Regression Analysis, Stochastic Calculus