 Built a propensity model for the revenue team to predict the likelihood of an opportunity to convert at an early stage by analyzing customer demographics, customer trading behavior and sentiment of the customer.  Developed a Referral Engine for refer and earn section using CatBoost algorithm to predict clients who have highest probability of referring, this project boosted the client activation rate from 1.5% to 5% in Q3 2021. Built an automated dashboard to analyse the activation matrix and introduced a weekly reporting system for the marketing team using PowerBI by publishing the visualizations. Worked with product team to analyze customer’s feedback from the reviews on company’s mobile application from Google Play store Built a Single Customer View by unifying the siloed data from multiple sources. Headed a project with Microsoft and a third-party vendor to redesign and re-structure data architecture of the company on Azure Cloud. Built a data dictionary using Azure resource (Data Catalog) which helped various stakeholders to discover, understand, and consume data sources in their data landscape Create documents on build process and flow, build script maintenance, user guide for developers using Jira and GitHub

• Extracting data from company’s CRM and cleaning it using Pandas library in Python.• Monitoring lead generation and lead conversion results against KPIs.• Built operational reporting in Tableau to find areas of improvement for hiring team resulting 40% improvement in overall team performance. • Identifying trends and opportunities which may impact on or enhance growth.

- Designed machine learning/deep learning models by extracting, cleaning and analyzing data from internal and external sources.- Implemented performance metrics to evaluate the accuracy of the modelsPROJECTS :-* Stock Market Prediction Using Numerical and Textual Analysis : (Packages : Tensorflow, Auto_ARIMA, Sklearn, Nltk, XgBoost )* Built COVID-19 Dashboard Using Tableau :1. Eliminating the hard-coding and manual sorts using a level of detail calculated field2. Detailed formatting with containers3. Container Swaps * Prediction Using Decision Tree Algorithm (Packages : Pandas, Numpy, Seaborn, Graphviz)