Overview
On Site
Depends on Experience
Full Time
Skills
Data Analysis
Data Science
Machine Learning (ML)
Extract
Transform
Load
Amazon Lambda
Amazon Redshift
Amazon SageMaker
Amazon Web Services
TensorFlow
Data Engineering
Job Details
Job Description
Responsibilities
- Analyze large, complex datasets to uncover trends, patterns, and insights. Perform exploratory data analysis (EDA) leveraging AWS data processing tools.
- Design, build, train, and evaluate machine learning models using AWS SageMaker and frameworks such as TensorFlow.
- Utilize AWS Glue, Redshift, Textract, and other data engineering tools to preprocess, clean, and transform data for machine learning workflows.
- Develop end-to-end, automated machine learning pipelines on AWS for seamless deployment and operationalization of models at scale.
- Work closely with data engineers, business analysts, and stakeholders to understand business requirements and customize data science solutions accordingly.
- Deploy models into production environments and implement monitoring systems to track model performance, accuracy, and reliability using SageMaker and AWS Lambda.
- Maintain clear documentation of models, methodologies, and results. Communicate findings effectively to stakeholders to support data-driven decisions.
Qualifications
- Proven experience in data analysis, machine learning model development, and deployment.
- Strong proficiency with AWS services including SageMaker, Glue, Redshift, Textract, Lambda, and associated data processing tools.
- Hands-on experience with machine learning frameworks such as TensorFlow.
- Solid understanding of ETL processes and data pipeline development.
- Excellent communication skills to collaborate with cross-functional teams and present findings.
- Bachelor s or Master s degree in Computer Science, Data Science, Statistics, or related field preferred.
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