Senior Data Scientist

As a Data Scientist, your role will involve the following responsibilities: - Predictive Modeling & Machine Learning - Develop and deploy machine learning models for forecasting, optimization, and predictive analytics. - Utilize tools such as AWS SageMaker, Bedrock, LLMs, TensorFlow, and PyTorch for model training and deployment. - Perform model validation, tuning, and performance monitoring. - Deliver actionable insights from complex datasets to support strategic decision-making. - Data Engineering & Cloud Computing - Design scalable and secure ETL pipelines using AWS Glue. - Manage and optimize data infrastructure in the AWS environment. - Ensure high data integrity and availability across the pipeline. - Integrate AWS services to support the end-to-end machine learning lifecycle. - Python Programming - Write efficient, reusable Python code for data processing and model development. - Work with libraries like pandas, scikit-learn, TensorFlow, and PyTorch. - Maintain documentation and ensure best coding practices. - Collaboration & Communication - Collaborate with engineering, analytics, and business teams to understand and solve business challenges. - Present complex models and insights to both technical and non-technical stakeholders. - Participate in sprint planning, stand-ups, and reviews in an Agile setup. Qualifications Required: - 5+ years of relevant experience in data science, predictive modeling, and machine learning. Preferred Experience (Nice to Have): - Experience with applications in the utility industry (e.g., demand forecasting, asset optimization). - Exposure to Generative AI technologies. - Familiarity with geospatial data and GIS tools for predictive analytics. - Experience working in cloud-based data science environments (AWS preferred). As a Data Scientist, your role will involve the following responsibilities: - Predictive Modeling & Machine Learning - Develop and deploy machine learning models for forecasting, optimization, and predictive analytics. - Utilize tools such as AWS SageMaker, Bedrock, LLMs, TensorFlow, and PyTorch for model training and deployment. - Perform model validation, tuning, and performance monitoring. - Deliver actionable insights from complex datasets to support strategic decision-making. - Data Engineering & Cloud Computing - Design scalable and secure ETL pipelines using AWS Glue. - Manage and optimize data infrastructure in the AWS environment. - Ensure high data integrity and availability across the pipeline. - Integrate AWS services to support the end-to-end machine learning lifecycle. - Python Programming - Write efficient, reusable Python code for data processing and model development. - Work with libraries like pandas, scikit-learn, TensorFlow, and PyTorch. - Maintain documentation and ensure best coding practices. - Collaboration & Communication - Collaborate with engineering, analytics, and business teams to understand and solve business challenges. - Present complex models and insights to both technical and non-technical stakeholders. - Participate in sprint planning, stand-ups, and reviews in an Agile setup. Qualifications Required: - 5+ years of relevant experience in data science, predictive modeling, and machine learning. Preferred Experience (Nice to Have): - Experience with applications in the utility industry (e.g., demand forecasting, asset optimization). - Exposure to Generative AI technologies. - Familiarity with geospatial data and GIS tools for predictive analytics. - Experience working in cloud-based data science environments (AWS preferred).