Abhishek Nishad

Responsible for data gathering, performing EDA and feature engineering using Python Pandas, Numpy, Seaborn. Implemented churn prediction model to identify customer at risk of leaving the Service. Built predictive models and machine learning algorithms to assess credit risk. Performed Sentiment Analysis on Feedback and Reviews by customers. Assisted in building a portfolio optimization tool to maximize returns.

Analyzing NRI customer data, and build models using Python, Pandas, Numpy, Scikit-Learn, Machine Learning to assess credit risk analysis. Developed insights and summarizations scripts using Python, SQL. Created Dashboards using Tableau to present insights to senior leaders. Collaborated with cross-functional teams including marketing, product, and operations to drive results.

Managed a portfolio of high-net-worth clients and developed strong relationships with them, resulting in a high level of customer satisfaction and loyalty. Conducted customer needs assessments and recommended appropriate banking solutions to meet their financial goals. By analyzing factors such as credit history, financial transactions, and investment patterns, banks can identify potential clients for upsell and also mitigate risks, such as money laundering, fraud, or non-compliance with regulations.

Analyzed customer data to identify cross-selling opportunities and increase revenue per account. Exceeded sales targets by 25% by implementing a new customer segmentation strategy and targeting high-potential accounts. Conducted market research and competitive analysis to inform strategic planning and product development.