About

Bharat Bajoria is an accomplished data science professional with a wealth of experience in Statistics, Machine Learning, and Deep Learning. With a Master's degree in Analytics from the Indian Institute of Science, Bharat has developed a strong analytics and research mindset that has helped him improve key business metrics in various industries. Bharat has worked in several domains, including Fin-Tech, IT, e-Commerce, and Fleet management, and has gained extensive experience in handling complex problems such as Multinomial Imbalanced Dataset Classification, Pipeline prediction with confidence intervals, statistical testing, text summarization, and Object detection. Bharat's tech stack exposure is extensive and includes Python (Pandas, Matplot, Scikit, Pytorch, etc.), SQL, AWS, and PySpark. He has also worked with various machine learning algorithms such as SVM, XGBoost, CNN, and RNN, and has developed expertise in object detection and deep learning. Currently, Bharat is a Senior Analyst at American Express AI Labs, where he is a key member of the team responsible for developing AI solutions that enhance customer experience and drive business growth. Prior to joining American Express, Bharat worked as a Data Scientist at Netradyne, where he tackled the Multinomial Imbalanced Dataset Classification problem and setup AWS EMR cluster environment to decrease computation time leveraging parallelization. Bharat has also worked as a Data Science Intern at Oracle, where he collaborated with the Global Business team to develop a predictive model using Random Forest Regressor to help the business unit predict candidate pipeline where Confidence Interval was built basis 2019 research paper by Zhang and Zimmerman on Random Forest Confidence Interval. Overall, Bharat has 2.85 years of relevant experience and has demonstrated a passion for using data science to solve complex business problems. His expertise in AI and machine learning, combined with his strong analytical skills, make him a valuable asset to any organization.