Anurag Sogani

I am an experienced Data Scientist with a strong background in keyword planning and credit risk modeling. In my current role at Datawrkz, I have engineered a proactive keyword planning solution that has achieved an 85% average forecasting accuracy. By employing various forecasting models, including the Random Forest algorithm and XGBoost, I analyze over 10,000 data points weekly to predict keyword performance. Additionally, I have incorporated search engine trends and social media analytics as additional data sources, resulting in a 15% enhancement over baseline models.

During my time at MyShubhLife, I enhanced the accuracy of the CRM predictive model by 10% using the Random Forest algorithm on NTC users' bank statement data. I also achieved a 50% increase in click rate through precise targeting using the Random Forest algorithm on promotional-marketing SMS data. I have a strong track record of collaborating across teams to validate model performance, optimize hyperparameters, and provide insights to refine credit risk assessment.

Prior to my current roles, I worked as an ML Engineer at Bitwise Academy, where I crafted a smart Discord chatbot in Python and Rasa. I also collaborated with the content team to curate training data for Rasa, enhancing the chatbot's responsiveness to user queries effectively. As an intern at Axis India ML Research Lab, I developed a generalized pre-processing framework for streamlined data transformation and implemented image augmentation techniques to optimize CNN model performance.