With the Cloud serving as an enabler, Data as a business driver, and AI as a core differentiator, we offer comprehensive, cost effective and value added services across a variety of industries such as Energy, Utilities, Healthcare and Real estate.
Job Summary:
We are looking for a highly skilled Senior Data Scientist to join our India-based team in a remote capacity. This role focuses on building and deploying advanced predictive models to influence key business decisions. The ideal candidate should have strong experience in machine learning, data engineering, and working in cloud environments, particularly with AWS. 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):
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.
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).
Machine Learning, Predictive Modeling, Data Engineering, Cloud Computing, AWS SageMaker, AWS Bedrock, AWS Glue, LLMs, TensorFlow, PyTorch, Jupyter Notebooks, Python, Pandas, Scikit-learn, Data Processing, ETL Pipelines, Model Training, Model Deployment, Model Validation, Performance Monitoring, Data Infrastructure Optimization, Generative AI, Geospatial Data, GIS Tools, Agile Methodologies, Communication Skills, Stakeholder Management