Job Description

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, Naive 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
You will be required to discuss and use various algorithms and approaches daily.
Leading the entire software lifecycle including hands-on development, code reviews, testing, deployment, and documentation. Agile SCRUM and MLOps experience is preferred.
Develop reusable/scalable assets and accelerators. Implement ML best practices.
Work directly with our internal technical teams to ensure that our solutions are seamlessly and effectively integrated
Analyse the market and industry trends in the technology and proactively look for opportunities in proposing the best solutions. Proactively research on upcoming ML techniques and best practices.
Responsible for coding, testing, debugging, evaluating solution/ technology options (including Cloud), and documenting application development
Migrate current analytics applications & pipelines to Cloud in future
Experience - 8-15 yrs
Qualification - Graduate with Engineering Degree (CS/Electronics/IT) / MCA / MCS + Masters in Statistics/Economics/Business Analytics

Skills Required