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# AWS Data Scientist

- **Company:** Capgemini
- **Location:** Atlanta, GA, United States
- **Experience:** Expert
- **Salary:** $80,786.0 - $90,892.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Business Analytics Applications, Data Analysis, Big Data, Cloud Engineering, Computer Programming, Data Security, Data Visualization, Python (Programming Language), Machine Learning, NumPy, Tensorflow, SQL Databases, Data Streaming, Feature Engineering, Pytorch, Apache Spark, Deep Learning, Pandas, Build Management, Scikit Learn, AWS Data Analytics, Machine Learning Operations, Software Version Control, Unsupervised Learning
- **Published:** July 11, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=9d078162c8ac8e2b

## About the Role

* Minimum 8+ years of experience in Data Science, AI, or Machine Learning
 * Strong hands-on expertise in AI & ML, including supervised and unsupervised learning, NLP, or deep learning
 * Advanced Python programming skills, including libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch
 * Extensive experience with AWS, especially SageMaker, S3, Redshift, Glue, Athena, Lambda
 * Strong foundation in statistics, predictive modeling, and ML algorithms
 * Proficiency in SQL and experience with data visualization techniques
 * Excellent communication and stakeholder management skills, * AWS Certifications (Machine Learning - Specialty or Solutions Architect)
 * Experience with big data technologies such as Spark
 * Exposure to real-time or streaming data pipelines
 * Background in financial services or regulated industries

## Description

We are looking for a highly experienced AWS Data Scientist with deep expertise in Artificial Intelligence (AI), Machine Learning (ML), and advanced Python programming to build and deploy scalable, cloud-native analytics solutions on AWS. The role requires hands-on experience across the full data science lifecycle and close collaboration with business and engineering teams., * Design, develop, and deploy AI/ML models and data science solutions on AWS

 * Build end-to-end ML pipelines using AWS services such as SageMaker, Lambda, EC2, and ECR
 * Perform advanced data analysis, feature engineering, model training, and optimization using Python
 * Work with large-scale datasets using AWS data services including S3, Glue, Athena, and Redshift
 * Implement MLOps practices for model deployment, monitoring, retraining, and version control
 * Translate complex business problems into AI/ML-driven solutions
 * Ensure adherence to data security, governance, and compliance standards


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