About

Rohit Gupta is a highly skilled and experienced data scientist with over 12 years of experience in the field. He is passionate about transforming data into meaningful stories and actionable insights. With a strong background in finance, healthcare, and telecom, Rohit has led and implemented multiple analytics projects throughout his career. Rohit is an expert in machine learning, deep learning, big data, Spark, NoSQL, cloud computing, and IoT. He has extensive knowledge of deep learning frameworks such as Keras, Caffe/Caffe2, TensorFlow, and PyTorch. Rohit is also proficient in NLP tasks such as text classification, topic modeling, named entity recognition, parts-of-speech tagging, relationship extraction, and stemming. He has hands-on experience developing neural networks and/or neural network operators. Rohit is skilled in a wide variety of DL network architectures spanning CNNs, RNNs/LSTMs, transformers/NLP, and more. He is proficient in Python programming and several of its libraries such as Pandas, NumPy, Scikit-learn, Scipy, Tensorflow, and Gensim. Rohit is also experienced in visualization/dashboarding tools such as Tableau. Rohit has expertise in data warehouse BI (SSIS/SSAS/SSRS), OLAP/ETL tools, and relational databases such as SQLServer and MongoDB. He has experience in big data technologies such as Spark Technology 2.0/Spark Streaming (Structured)/Spark Mlib (Machine learning) and cloud computing services such as AWS (Amazon Web Services), AWS Cloud Services like AWS S3, AWS Redshift, Kensis EC2, EMR, Data pipeline, RDS, Google Cloud, and Microsoft Azure Services. Rohit has worked for leading companies such as AMEX, Xerox, and Orange Business Services. He has experience in building chatbot recommendations for users and has worked on projects such as document classification and defaulter analysis. Rohit holds a Certificate in Leadership Excellence in Organization Leadership from Harvard Business School and a Bachelor of Technology in Computer Science from Ideal Institute of Technology. He is proficient in a wide range of technologies such as ML, AI, Deep Learning, Spark, AWS, NLP, SQL, Random Forest, Azure, Recommendation system, Big Data, SVM, Tensorflow, RNN, XGBoost, CNN, Python, Keras, Neural Networks, Hadoop, HDFS, Word2