Tushar Chakraborty

Utilized statistical methods to analyse data and generate actionable insights for product development. Employed Python (Pandas, NumPy) and SQL for data extraction, cleaning, and manipulation. Assisted in the development and validation of predictive machine learning models. Gained hands-on experience with ML libraries such as Scikit-learn, TensorFlow, and Keras. Contributed to feature engineering processes to optimize model performance. Worked closely with product managers and developers to integrate machine learning functionalities into product features. Provided data-driven recommendations for product improvements and enhancements. Supported the design and analysis of A/B tests to measure the impact of new features and optimizations. Assisted in interpreting results and recommended subsequent actions based on the data.

Experience in modelling with statistical techniques such as – linear regression, logistic regression, ANCOVA, XG-Boost, Time series – ARIMA, ML interpretability and bias algorithms etc. Building Machine Learning and/or statistical models that evaluate the legitimacy and track improvement over time. Analysing the reporting needs & Using Business Objects, generated reports aligned in accordance with user specifications, by understanding the system improved the retrieving performance of the reports. Conceptualizing and creating reports and dashboarding solutions. Identifying, analysing and interpreting trends and patterns in complex data sets using statistical techniques and generated actionable insights. Worked on Credit Risk- PD/LGD Models. Optimization Techniques using Operation Research Models. Numerical Analysis- Newton Raphson, Simpson’s Rule, Back Propagation using Deep Learning etc.