AWS SageMaker Data Scientist

Position Title : AWS SageMaker Data Scientist Location : Charlotte, NC (Onsite/Hybrid) Experience : 8+ Years Employee Type : Full Time with Benefits Job Description We are seeking a highly skilled AWS SageMaker Data Scientist with deep expertise in building, deploying, and optimizing machine learning solutions on AWS. The ideal candidate will have strong experience with modern ML architectures (including transformers), end-to-end pipeline development, and ML Ops best practices across the AWS ecosystem. This role requires a hands-on technologist who can collaborate with cross-functional teams to translate business needs into scalable AI/ML solutions. Must Have skills: 8+ years of hands-on experience in data science, machine learning, or applied AI. Strong expertise in transformer models , ML architectures, and algorithm development. Proven experience with Amazon SageMaker, AWS Bedrock, and MLflow . Advanced programming skills in Python or R . Experience with AWS analytical and data services including Athena, Redshift, EMR, Glue, and Lambda . Key Responsibilities: Design and implement end-to-end machine learning (ML) pipelines using services such as Amazon SageMaker, AWS Glue, AWS Lambda, and Amazon S3 . Perform data collection, cleaning, and feature engineering to prepare datasets for modeling. Develop predictive models and statistical analyses using Python, R, or similar tools . Deploy, monitor, and optimize ML models in production environments using AWS ML Ops best practices. Collaborate with data engineers to design ETL pipelines and ensure data availability and reliability. Utilize AWS analytics services (Athena, Redshift, QuickSight, EMR) for advanced reporting and visualization. Work with stakeholders to translate business objectives into data science solutions and actionable insights. Apply AI/ML algorithms for use cases such as forecasting, anomaly detection, NLP, computer vision , and recommendation systems. Maintain compliance with security and governance standards for data management on AWS.