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AWS Data Scientist

Job in Malvern, Chester County, Pennsylvania, 19355, USA
Listing for: Diverse Lynx
Full Time position
Listed on 2026-08-26
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Scientist, AWS
Salary/Wage Range or Industry Benchmark: 53 - 59 USD Hourly USD 53.00 59.00 HOUR
Job Description & How to Apply Below
Location: Malvern

AWS Data Scientist

Location:

Malvern, PA

Duration: 6 Months

Pay Rate: $53–59/hr. on W2

Experience:

8+ Years

We 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 Sage Maker, Amazon Bedrock, Python, and AWS Analytics services, along with a solid background in building production-grade machine learning pipelines and GenAI applications.

Key Responsibilities

  • Design, develop, train, deploy, and monitor machine learning models using Amazon Sage Maker.
  • Build and optimize scalable AI/ML solutions leveraging AWS cloud services.
  • Develop data processing and analytics workflows using Python, SQL, Pandas, Num Py, and Scikit-learn.
  • Implement predictive models, feature engineering, statistical analysis, and data preparation.
  • Build and maintain MLOps pipelines using Sage Maker Pipelines, CI/CD, Docker, and Git Hub.
  • Develop and integrate Generative AI solutions using Amazon Bedrock, Sage Maker Jump Start, and Retrieval-Augmented Generation (RAG) frameworks.
  • Utilize AWS services including S3, Glue, Athena, Redshift, Lambda, and Cloud Watch 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 Skills

  • 8+ years of experience in Data Science, Machine Learning, and AI.
  • Strong hands-on experience with Amazon Sage Maker.
  • Proficiency in Python, SQL, Pandas, Num Py, Scikit-learn, Tensor Flow, and PyTorch.
  • Experience with AWS Analytics services including S3, Glue, Athena, Redshift, Lambda, and Cloud Watch.
  • Expertise in Machine Learning, Predictive Modeling, Feature Engineering, and Statistical Analysis.
  • Strong experience with MLOps, Sage Maker Pipelines, CI/CD, Docker, and Git Hub.
  • Experience with Generative AI, Large Language Models (LLMs), Amazon Bedrock, Sage Maker Jump Start, and RAG.
  • Exposure to Arize AI or similar AI/ML model monitoring and observability tools.
  • Strong analytical, troubleshooting, and problem-solving skills.
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