Responsibilities: 5-8+ years of hands-on experience in data science and AI/ML Use predictive modelling to increase and optimize power generation, price, cost savings, customer experiences and other business outcomes Experience in statistical modelling, machine learning, probability theory, algorithms. data mining, unstructured data analytics and natural language processing Expertise in machine learning techniques such as Clustering, Regression, Bayesian methods, tree-based learners, SVM, RF, XGBOOST, time series modelling, dimensionality reduction, SEM, GLM, GLMM, Deep learning, Neural Network, Topic Modelling, Multivariate Statistics, K-NN, Nave Bayes etc. Working knowledge of popular Deep Learning architectures and theory, simulation, scenario analysis, constraint optimization, anomaly detection, semi-supervised machine learning, unsupervised learning algorithms using deep learning etc. Experience with optimization techniques (Linear Programming, Genetic Algorithm, Sim. Annealing, MC Simulation) Experience in one of the upcoming technologies like deep learning, NLP, NLG, image processing, recommender systems, chatbot, voice AI, video AI etc. Experience of working on end-to-end data science pipeline: problem scoping, data discovery and extraction, EDA, modelling, evaluation, insights, visualizations, continuous improvement, maintenance, and business value/impact tracking. Problem-solving: Ability to break the problem into small parts and applying relevant techniques to drive required outcomes. Responsible for coding, testing, debugging, evaluating solution/ technology options (including Cloud), and documenting application development