- 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, Naïve 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
