-Created a Product Recommendation Engine from scratch using Machine Learning models which reduced the organization cost by 40%, lead to improved sales, helped in target marketing and customer acquisition.-Employed SQL to analyze customer data, enabling data- driven product recommendations and enhancing overall customer satisfaction.-Conducted data cleansing and dimensionality reduction on a large FAT dataset which helped in improved data quality, elimination of data outliers, reduced Overfitting, and enhanced model efficiency for subsequent analysis and decision-making.-Eliminated data bias and reduced skewness through Z- score Normalization and regression techniques, leading to improved data quality and more accurate analysis.-Applied supervised & unsupervised algorithm (k-means) along with Association rules (apriori) resulting in refined recommendations for the customers.

-Deployed Neural Networks, Decision Trees and Ensembles to identify fraudulent customers, leading to improved fraud prevention and reduced financial losses.-Applied machine learning models for customer analytics and data mining, resulting in a 15% increase in customer retention rates and a 20% boost in sales revenue through personalized marketing strategies.-Employed data visualization techniques to simplify intricate financial data, empowering stakeholders to make informed decisions, optimize resources, and manage risks effectively.-Acted as a liaison between stakeholders and the development team to identify business needs and validate them using SQL.-Project Management Skills: Agile, People management, Performance evaluation, mentoring, Knowledge Transfer, Hiring.

-Developed a neural network model using Rapid Miner, achieving an 85% accuracy rate in predicting customer churn.-Generated impactful data insights through interactive Tableau visualizations, employing advanced charts for trend analysis and data insights which ultimately led to a two-thirds reduction in processing time.

-Analyzed large datasets, developed dashboards, and proposed recommendations for KPI tracking, leading to improved data-driven decisions and enhanced performance monitoring.-Extracted, cleansed, and transformed data into interactive Tableau visualizations, improving data accessibility and enabling informed decisions.-Prepared report backgrounds, conducted requirement gathering using agile methodology and analyzed complex datasets, contributing to the organization's data-driven insights.