AWS Data Scientist

AWS Data ScientistLocation: Malvern, PADuration: 6 MonthsPay Rate: $53–59/hr. on W2Experience: 8+ YearsWe are seeking an experienced AWS Data Scientist with strong expertise in Machine Learning, MLOps, and Generative AI to design, develop, deploy, and optimize scalable AI/ML solutions on AWS. The ideal candidate should have hands-on experience with Amazon SageMaker, Amazon Bedrock, Python, and AWS Analytics services, along with a solid background in building production-grade machine learning pipelines and GenAI applications.Key ResponsibilitiesDesign, develop, train, deploy, and monitor machine learning models using Amazon SageMaker.Build and optimize scalable AI/ML solutions leveraging AWS cloud services.Develop data processing and analytics workflows using Python, SQL, Pandas, NumPy, and Scikit-learn.Implement predictive models, feature engineering, statistical analysis, and data preparation.Build and maintain MLOps pipelines using SageMaker Pipelines, CI/CD, Docker, and GitHub.Develop and integrate Generative AI solutions using Amazon Bedrock, SageMaker JumpStart, and Retrieval-Augmented Generation (RAG) frameworks.Utilize AWS services including S3, Glue, Athena, Redshift, Lambda, and CloudWatch for data engineering and model deployment.Monitor model performance and observability using Arize AI or similar monitoring platforms.Collaborate with cross-functional teams to deliver scalable, production-ready AI/ML solutions.Required Skills8+ years of experience in Data Science, Machine Learning, and AI.Strong hands-on experience with Amazon SageMaker.Proficiency in Python, SQL, Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch.Experience with AWS Analytics services including S3, Glue, Athena, Redshift, Lambda, and CloudWatch.Expertise in Machine Learning, Predictive Modeling, Feature Engineering, and Statistical Analysis.Strong experience with MLOps, SageMaker Pipelines, CI/CD, Docker, and GitHub.Experience with Generative AI, Large Language Models (LLMs), Amazon Bedrock, SageMaker JumpStart, and RAG.Exposure to Arize AI or similar AI/ML model monitoring and observability tools.Strong analytical, troubleshooting, and problem-solving skills.