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
Skills Required
- 8-15 years of relevant experience
- Graduate with Engineering Degree (CS/Electronics/IT) or MCA/MCS; Masters in Statistics/Economics/Business Analytics
- Experience in statistical modelling, machine learning, probability theory, algorithms, data mining, unstructured data analytics, and NLP
- Expertise with ML techniques: clustering, regression, Bayesian methods, SVM, RF, XGBOOST, time series modelling, dimensionality reduction, SEM, GLM, GLMM, deep learning, neural networks, topic modelling, K-NN, Naive Bayes, multivariate statistics
- Working knowledge of deep learning architectures, simulation, scenario analysis, constraint optimization, anomaly detection, semi-supervised and unsupervised deep learning
- Experience with optimization techniques (Linear Programming, Genetic Algorithms, Simulated Annealing, Monte Carlo Simulation)
- Experience with emerging technologies: deep learning applications, NLP/NLG, image processing, recommender systems, chatbots, voice AI, video AI
- Proven experience across end-to-end data science pipeline: problem scoping, data discovery/extraction, EDA, modelling, evaluation, visualization, deployment, maintenance, and impact tracking
- Lead software lifecycle with hands-on development, code reviews, testing, deployment, and documentation
- Develop reusable/scalable assets and implement ML best practices
- Ability to work directly with internal technical teams to integrate solutions
- Analyze market and technology trends and proactively research new ML techniques and best practices
- Responsible for coding, testing, debugging, evaluating solution/technology options (including Cloud), and documenting application development; migrate analytics pipelines to Cloud in future
- MLOps experience
- Agile SCRUM experience
What We Do
Hudson Information Technology and Manpower Services, part of The Hudson Group, is a global workforce solutions and software services partner founded in 2019. The company combines HudsonIT Consultancy Ltd, which provides enterprise software and technology consulting, with Hudson Manpower Inc, which specializes in comprehensive technical recruitment across various sectors, including Oil & Gas, IT, and Hospitality.
