Data Scientist

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Job Summary:

Senior Data Scientist

You'll be collaborating closely with cross-functional teams to design, develop, and deploy cutting-edge ML models using tools like SageMaker, Bedrock, PyTorch, TensorFlow, Jupyter Notebooks, and AWS Glue. This is a fantastic opportunity to work on impactful AI/ML solutions within a dynamic and innovative team.

Key Responsibilities:

Predictive Modeling & Machine Learning

• Develop and deploy machine learning models for forecasting, optimization, and predictive analytics.

• Use 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

• Work 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.

Preferred Experience (Nice to Have):

utility industry

Generative AI

geospatial data and GIS tools

Qualifications:

• Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or a related field.

• 5+ years of relevant experience in data science, predictive modeling, and machine learning.

• Experience working in cloud-based data science environments (AWS preferred).