Currently I am pursuing M.Sc. (Applied Statistics and Analytics) from NMIMS. I have a working experience of around 18 months at Nielsen. I have gained hands on experience at using Statistical techniques like Sampling and estimation for calculating the optimum sample for cities and villages and estimating the universe of stores using the ratio estimate method. Automation of BAU activities which includes logic check, trend check and other QC parameters for census data using R. Instrumental in managing and handling RMS data and conducting research to ensure delivery of quality reports to the FMCG clients. Analyzing and visualizing for trend check of estimated sales using Spotfire. While working as an intern at Hopstoch.in I was instrumental in creating SQL queries for our clients for uploading delivery status & helping them with reports/KPI in excel on daily basis. Coordinating with their finance team and understanding their requirements and executing them in SQL. Providing timely and error free reports to understand the business need using EXCEL and SQL. Understanding our company?s data and analyzing according to the requirement and executing on SQL for desired output. I also got an opportunity on working a live project for of Business Optimization for Charcoal Biryani (Online Food Joint). Helping Charcoal Biryani to dig deep into their business by providing them with different customer segments based on customer\'s Frequency, Recency, Engagement, Value so that they can run different campaigns for different segments of customer\'s. In addition to this through Principal Component Analysis we allot tiers to segment and design loyalty program for top tier customers. We have also done Market Basket Analysis to check for most combination of products that is been purchased. I have also worked on a Research paper of Impact of Urbanisation on biodiversity. The purpose of the study was to understand how the factors contributing towards urbanisation have an impact on biodiversity through descriptive and exploratory analysis. To cluster and identify countries which fall in the same category of urbanisation and the impact which it has on biodiversity. To understand how biodiversity behaves in countries which are most urbanised against the countries that are least urbanised through K-Means clustering technique. We also build a Multiple Linear Regression model to predict the change in biodiversity through various factor of urbanisation. To understand which all factors of urbanization should be considered to help flourish biodiversity.