Data Scientist Engineer

Role Summary: Looking for one data scientist engineer with Strong experience in AI/ML, Data collection preprocessing, estimation, Architecture creation Responsibility: Model Development: Design and implement ML models to tackle complex business challenges. Data Preprocessing: Clean, preprocess, and analyze large datasets for meaningful insights and model features. Model Training: Train and fine-tune ML models using various techniques including deep learning and ensemble methods. Evaluation and Optimization: Assess model performance, optimize for accuracy, efficiency, and scalability. Deployment: Deploy ML models in production, monitor performance for reliability. Collaboration: Work with data scientists, engineers, and stakeholders to integrate ML solutions. Research: Stay updated on ML/AI advancements, contribute to internal knowledge. Documentation: Maintain comprehensive documentation for all ML models and processes. Qualification - Bachelor's or masters in computer science, Machine Learning, Data Science, or a related field and must be experience of 6-10 years. Desirable Skills: Must Have 1. Experience in timeseries forecasting, regression Model, Classification Model 2. Python , R, Data analysis 3. Large size data handling with Panda , Numpy and Matplot Lib 4. Version Control: Git or any other 5. ML Framework: Hands on exp in Tensorflow, Pytorch, Scikit-Learn, Keras 6. Good knowledge on Cloud platform and ( AWS/ AZure/ GCP), Docker kubernetis 7. Model Selection, evaluation, Deployment, Data collection and preprocessing, Feature engineering Estimation Good to Have Experience with Big Data and analytics using technologies like Hadoop, Spark, etc. Additional experience or knowledge in AI/ML technologies beyond the mentioned frameworks. BFSI and banking domain Role Summary: Looking for one data scientist engineer with Strong experience in AI/ML, Data collection preprocessing, estimation, Architecture creation Responsibility: Model Development: Design and implement ML models to tackle complex business challenges. Data Preprocessing: Clean, preprocess, and analyze large datasets for meaningful insights and model features. Model Training: Train and fine-tune ML models using various techniques including deep learning and ensemble methods. Evaluation and Optimization: Assess model performance, optimize for accuracy, efficiency, and scalability. Deployment: Deploy ML models in production, monitor performance for reliability. Collaboration: Work with data scientists, engineers, and stakeholders to integrate ML solutions. Research: Stay updated on ML/AI advancements, contribute to internal knowledge. Documentation: Maintain comprehensive documentation for all ML models and processes. Qualification - Bachelor's or masters in computer science, Machine Learning, Data Science, or a related field and must be experience of 6-10 years. Desirable Skills: Must Have 1. Experience in timeseries forecasting, regression Model, Classification Model 2. Python , R, Data analysis 3. Large size data handling with Panda , Numpy and Matplot Lib 4. Version Control: Git or any other 5. ML Framework: Hands on exp in Tensorflow, Pytorch, Scikit-Learn, Keras 6. Good knowledge on Cloud platform and ( AWS/ AZure/ GCP), Docker kubernetis 7. Model Selection, evaluation, Deployment, Data collection and preprocessing, Feature engineering Estimation Good to Have Experience with Big Data and analytics using technologies like Hadoop, Spark, etc. Additional experience or knowledge in AI/ML technologies beyond the mentioned frameworks. BFSI and banking domain