About

Harish Goud is a skilled MLE with over 2.5 years of industry experience in the BFSI domain. He is currently working at Credit Suisse as an ENO, where he is responsible for developing risk models in the Quantitative Analysis and Technology team. Harish is proficient in a range of programming languages, including Python (with ML libraries), C/C++, and Java (Core). Harish has a strong background in machine learning, with expertise in both classical and deep learning algorithms. He is well-versed in supervised algorithms such as SVM, decision trees, and Xgboost, as well as unsupervised algorithms like K-means and PCA. Additionally, Harish has experience working with artificial neural networks (ANN), convolutional neural networks (CNN), and recurrent neural networks (RNN). He is also proficient in time series forecasting techniques, including Holts winter and SARIMAX. Harish is well-versed in cloud technologies, including AWS Sagemaker, S3, Lambda, EC2, and Step functions. He has experience working with databases such as Neptune DB (SPARQL) and SQL, and is skilled in data visualization using PowerBI. Harish has previously worked at Quantiphi as a Machine Learning Engineer and at Publicis Sapient as an Engineering Trainee. He holds a Bachelor of Engineering degree in Computer Science from Birla Institute of Technology and Science, Pilani. Harish's technical skillset includes ML, AI, SQL, AWS, SVM, XGBoost, Big Data, Sagemaker, CNN, RNN, Deep Learning, Python, Java, and C. His experience and expertise make him a valuable asset to any team working in the field of machine learning and artificial intelligence.