Senior Data Scientist - Predictive Modeling & Machine Learning

As a Data Scientist in our team, you will be responsible for the following: - Predictive Modeling & Machine Learning: - Develop and deploy machine learning models for forecasting, optimization, and predictive analytics using tools such as AWS SageMaker, Bedrock, LLMs, TensorFlow, and PyTorch. - Perform model validation, tuning, and performance monitoring to ensure the accuracy and efficiency of the models. - Deliver actionable insights from complex datasets to support strategic decision-making. - Data Engineering & Cloud Computing: - Design scalable and secure ETL pipelines using AWS Glue to manage and optimize data infrastructure in the AWS environment. - Ensure high data integrity and availability across the pipeline by integrating AWS services to support the end-to-end machine learning lifecycle. - Python Programming: - Write efficient, reusable Python code for data processing and model development, working with libraries like pandas, scikit-learn, TensorFlow, and PyTorch. - Maintain documentation and ensure best coding practices to enhance the efficiency of the development process. - Collaboration & Communication: - Work collaboratively with engineering, analytics, and business teams to understand and solve business challenges effectively. - Present complex models and insights to both technical and non-technical stakeholders to facilitate informed decision-making. - Participate actively in sprint planning, stand-ups, and reviews within an Agile setup to ensure smooth project execution. 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 in our team, you will be responsible for the following: - Predictive Modeling & Machine Learning: - Develop and deploy machine learning models for forecasting, optimization, and predictive analytics using tools such as AWS SageMaker, Bedrock, LLMs, TensorFlow, and PyTorch. - Perform model validation, tuning, and performance monitoring to ensure the accuracy and efficiency of the models. - Deliver actionable insights from complex datasets to support strategic decision-making. - Data Engineering & Cloud Computing: - Design scalable and secure ETL pipelines using AWS Glue to manage and optimize data infrastructure in the AWS environment. - Ensure high data integrity and availability across the pipeline by integrating AWS services to support the end-to-end machine learning lifecycle. - Python Programming: - Write efficient, reusable Python code for data processing and model development, working with libraries like pandas, scikit-learn, TensorFlow, and PyTorch. - Maintain documentation and ensure best coding practices to enhance the efficiency of the development process. - Collaboration & Communication: - Work collaboratively with engineering, analytics, and business teams to understand and solve business challenges effectively. - Present complex models and insights to both technical and non-technical stakeholders to facilitate informed decision-making. - Participate actively in sprint planning, stand-ups, and reviews within an Agile setup to ensure smooth project execution. 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).