Nityo Infotech
AWS Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AWS Data Scientist with a contract length of "Unknown," offering a pay rate of "Unknown." It requires 10+ years in Data Science, strong AWS expertise, advanced Python skills, and proficiency in SQL and data visualization.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
June 3, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Charlotte, NC
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🧠 - Skills detailed
#AWS (Amazon Web Services) #SageMaker #Statistics #SQL (Structured Query Language) #Supervised Learning #Deployment #S3 (Amazon Simple Storage Service) #Programming #EC2 #Visualization #Data Analysis #Pandas #Deep Learning #Monitoring #Model Deployment #Python #PyTorch #ECR (Elastic Container Registery) #Predictive Modeling #NLP (Natural Language Processing) #Unsupervised Learning #Version Control #Athena #Datasets #Data Science #ML (Machine Learning) #TensorFlow #NumPy #Lambda (AWS Lambda) #AI (Artificial Intelligence) #Redshift #Libraries
Role description
Required Skills & Qualifications
• Minimum 10+ 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
Key Responsibilities
• 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
Required Skills & Qualifications
• Minimum 10+ 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
Key Responsibilities
• 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
