About

Rahul Anand is a highly skilled Senior Data Scientist with over 9 years of experience in the field of Machine Learning, Natural Language Processing, and Deep Learning. He is currently working at IBM as a Data Scientist, where he has been utilizing his expertise in Cloudant, DB2, Cirrus Cloud, IBM Watson, Python, Pandas, Scikit Learn, EDA, and other tools to develop recommendation engines and other data-driven solutions. Prior to joining IBM, Rahul has worked as a Principal Development Engineer at Calsoft and NetApp, where he was responsible for developing On-Command Unified Manager for NetApp flash storage monitoring device OnTap. He has also been involved in all important discussions of implementing recommendation engines for OCUM, preparation of development plans, and the preparation of new matrix, symptom definitions, alerts, and reports. Rahul has utilized his skills in Python, Machine Learning algorithms, Deep Learning, IR, AI, ML, Artificial Intelligence, PCA, TSNE, TF-IDF, BOW, Linear Regression, NR, K-NN, CNN, K-Means, SVM, DT, DBSCAN, Xgboost, RF, Tensorflow, NumPy, SciPy, Pandas, and Data Science to develop and maintain various features for the products. Rahul has a Bachelor of Technology (B.Tech.) degree in Information Technology from M.L.V Textile and Engineering College and has completed his PGC in AI for Digital Business & Ecommerce from Wileynxt IIT Roorkee. He has also completed industrial training in CCNA and CCNP from R.N.S Infotech and Zoom Technology Hyderabad, respectively. Rahul's technical skills include Data Scientist, Research Scientist, AWS, NLP, ML, Python, Pytorch, Scikit, Pandas, MongoDB, AI, Deep Learning, Computer Vision, Hadoop, Elastic Search, Flask, SVM, XGBoost, CNN, Tensorflow, and Java. Rahul is seeking a challenging role in the IT industry as a Machine Learning/Data Scientist, where he can contribute to the company's growth while ensuring personal growth. With his dedication, expertise, and talent, Rahul aims to bring a sharper edge to the organization within the industry.