About

Riya Gupta is a highly skilled data scientist with over 6 years of relevant experience in solving complex data challenges across various industries such as Financial Services, FMCG, Marketing, and Telecommunications. She has a strong background in predictive modeling, customer churn prediction, classification, segmentation, and anomaly detection using statistical and machine learning techniques. She is experienced in Agile/Scrum methodology and has a proven track record of delivering high-quality projects on time. Riya holds a Master of Science degree in Economic Sciences (Econometrics) from the Indian Institute of Technology, Kanpur. She has worked with top-tier companies such as Fractal Analytics and Edelweiss, where she developed end-to-end, fault-tolerant forecasting pipelines using deep neural network classifiers, parallel processing, and Apache Spark frameworks. She has also designed uncertainty modeling tools to correct for COVID-19 impact on turnover. At Fractal Analytics, Riya developed a forecasting pipeline that extracts data from Azure Data Lakes, sends it into the forecast engine, collects the output, and uses a PowerBI dashboard and a ‘What-If’ simulator tool as visual interfaces. She used object-oriented algorithms to create model and ensemble objects in Python and implemented variable selection using Mutual Information and Ridge regularization in multivariate models. She also used Twitter’s Anomaly Detection algorithm for outlier treatment and a Bayesian Structural Time Series (BSTS) mechanism to create baseline forecasts. At Edelweiss, Riya solved salient business problems such as survival analysis to determine Customer Lifetime Value, building a comprehensive model to assess measures impacting productivity of client-facing advisory team, estimating potential revenue-generating capacity of clients, and segmentation of client pool for designing targeted marketing strategies for loan-based products of varying degrees of risk and returns. Riya has a strong tech stack that includes Data Scientist, Research Scientist, Databricks, Random Forest, Spark, Python, Azure, ML, Keras, Tensorflow, and Neural Networks. She is a dedicated professional who is passionate about using data science to solve complex business problems and drive positive outcomes.