About

Amit Rai Chowdhury is an accomplished Senior Data Scientist with over 16 years of experience in leveraging machine learning to solve complex business problems. He possesses exceptional technical, analytical, and presentation skills gained from working with top-notch global firms. Currently, he is working with Honeywell as a Senior Data Scientist, leading a team to develop a product for anomaly and fraud detection for vendor payments, which could potentially save Honeywell millions of dollars in fines for non-compliance. Amit's key skills include Python, Domino, Databricks, Airflow, Dremio, Bitbucket and Git (version control), R, SAS, Mainframes, Machine Learning (Classification, Regression, Clustering, Recommender Systems, Forecasting), Deep Learning (Neural Networks – ANN / CNN / RNN, Tensorflow, Pytorch, Transfer Learning, Transformers), Natural Language Processing (Sentiment Analysis, Neural machine translation, Encoder-Decoder models, BERT, Named Entity Recognition (NER), Topic modelling, Text mining, NLTK, SpaCy, Gensim), Computer Vision (Object detection and localization, Semantic Segmentation), and Big data processing and predictive modeling using Apache Spark (Pyspark, MLlib, Spark SQL). He has diverse experience working in domains such as Banking, Brokerage, Insurance, Retail, and Industrial. Before joining Honeywell, Amit worked as a Data Scientist at Thoucentric and Fractal Analytics, where he delivered several successful projects, including reducing paint defects for a car manufacturer, building a fuzzy text matching algorithm for partial address matching across multiple systems, and designing a recommender system using collaborative filtering for sales upselling and cross-selling. Amit has a Master of Business Administration (MBA) from the Indian Institute of Management (IIM), Lucknow, a Master of Computer Applications (MCA) from Amity University, and a B.Sc. (Hons.) in Physics from Delhi University. He is proficient in AWS, XGBoost, NLP, Python, SQL, Deep Learning, Spark, Object detection, BERT, Sentiment Analysis, Tensorflow, Computer Vision, Object Detection, Sagemaker, Databricks, CNN, RNN, Random Forest, Apache Airflow, Big Data, Neural Networks, Pytorch, AI, OpenCV, and Search.