Romee Panchal

Background

About Romee Panchal

As a seasoned Data Scientist, I have a proven track record of driving revenue growth and enhancing customer experiences by building risk models, behaviour models, and ML pipelines. With over 7 years of experience in the data science and machine learning field, I have consistently delivered impactful solutions in fintech, manufacturing, and other industries. My passion lies in leveraging data and advanced analytics to drive strategic decision-making and improve business outcomes.At PayU Finance, I have successfully developed and deployed risk models to predict the risk of new and repeat customers, enabling the whitelisting of 20 million users for BNPL products. Additionally, I created a customer lifetime value estimation product using existing models. I have also developed a scalable ML pipeline, processing data for over 350 million users and generating prediction scores.Furthermore, I have a strong background in model monitoring, having developed a framework to periodically check models in production for drift and performance metrics. This ensures the reliability and accuracy of the models over time.During my tenure at Tiger Analytics, I worked on a wide range of projects, including developing an early warning system for a banking client to predict defaults in advance and creating propensity models for personal loan sales. I also gained expertise in data extraction and ETL processes, as well as implementing an auto-machine learning framework for anomaly detection and forecasting.I hold a Bachelor of Engineering in Computer Science from Gurukul Kangri University. With my strong analytical and problem-solving skills, coupled with my ability to thrive in fast-paced environments, I am committed to driving data-driven solutions and contributing to the success of organizations.I possess a strong skill set in machine learning, data analysis, and deep learning. My programming expertise includes Python, R, and SQL, and I am also familiar with tools such as Docker, Git, and PySpark. I have experience working with AWS for cloud-based solutions. In terms of data manipulation and visualization, I am proficient in using Pandas, NumPy, Dask, Matplotlib, Seaborn, and Plotly. Additionally, I am well-versed in scikit-learn for machine learning tasks and PyTorch for deep learning applications.