
AWS + Data Science Professional
22 hours ago
Role Overview:
An AWS SME with a Data Science Background is responsible for leveraging Amazon Web Services (AWS) to design, implement, and manage data-driven solutions. This role involves a combination of cloud computing expertise and data science skills to optimize and innovate business processes.
Key Responsibilities:
- Data Analysis and Modelling: Analyzing large datasets to derive actionable insights and building predictive models using AWS services like SageMaker, Bedrock, Textract etc.
- Cloud Infrastructure Management: Designing, deploying, and maintaining scalable cloud infrastructure on AWS to support data science workflows.
- Machine Learning Implementation: Developing and deploying machine learning models using AWS ML services.
- Security and Compliance: Ensuring data security and compliance with industry standards and best practices.
- Collaboration: Working closely with cross-functional teams, including data engineers, analysts, DevOps and business stakeholders, to deliver data-driven solutions.
- Performance Optimization: Monitoring and optimizing the performance of data science applications and cloud infrastructure.
- Documentation and Reporting: Documenting processes, models, and results, and presenting findings to stakeholders.
Skills & Qualifications
Technical Skills:
- Proficiency in AWS services (e.g., EC2, S3, RDS, Lambda, SageMaker).
- Strong programming skills in Python.
- Experience with AI/ML project life cycle steps.
- Knowledge of machine learning algorithms and frameworks (e.g., TensorFlow, Scikit-learn).
- Familiarity with data pipeline tools (e.g., AWS Glue, Apache Airflow).
- Excellent communication and collaboration abilities.
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