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Data Scientist With Sagemaker Jobs (NOW HIRING)

Ztek Consulting INC

Data Scientist

Charlotte, NC · On-site

Collaborate with data engineers to design ETL pipelines and ensure data availability and ... SageMaker AWS Glue AWS Lambda and Amazon S3 * Perform data collection cleaning and feature ...

neptune technologies

Data Scientist

Duluth, GA

Position Summary As a Data Scientist, you will be responsible for developing and implementing ... Experience with AWS services (SageMaker, Lambda, S3, Redshift). • Preferred: Experience with deep ...

Neptune

Data Scientist

Duluth, GA · On-site

Position Summary As a Data Scientist, you will be responsible for developing and implementing ... Experience with AWS services (SageMaker, Lambda, S3, Redshift). • Preferred: Experience with deep ...

SWBC

Data Scientist II

San Antonio, TX · On-site

The Data Scientist II is expected to independently lead analyses and model development projects ... SageMaker, S3) and Snowflake. * Familiarity with MLOps tools and practices, including MLflow ...

VTG

Data Scientist

Beavercreek, OH

The Data Scientist will design, prototype, and implement a data management and application ... Experience with AI/ML development tools and libraries (e.g. Sagemaker, ML Studio, Tensorflow, Keras ...

SWBC

Data Scientist II

San Antonio, TX · On-site

... SageMaker, S3) and Snowflake. • Familiarity with MLOps tools and practices, including MLflow, experiment tracking, and model versioning. • Proficiency in Hex for data science experimentation and ...

Staffingine LLC

Data Scientist

San Francisco, CA · On-site

Contract * 50% - Consulting with internal teams (economists, analysts) to design and implement AI ... Implement solutions using AWS AI services (Bedrock, SageMaker, Textract, Databricks etc.) * Ensure ...

SWBC

Data Scientist II

San Antonio, TX · On-site

The Data Scientist II is expected to independently lead analyses and model development projects ... SageMaker, S3) and Snowflake. * Familiarity with MLOps tools and practices, including MLflow ...

Swbc

Data Scientist II

San Antonio, TX · On-site

The Data Scientist II is expected to independently lead analyses and model development projects ... SageMaker, S3) and Snowflake. * Familiarity with MLOps tools and practices, including MLflow ...

Staffingine LLC

Data Scientist

Redmond, WA · On-site

We are looking for a Data Scientist with strong experience in Python, SQL, and Machine Learning. The candidate should be comfortable working with large datasets, building predictive models, and ...

GRVTY

Data Scientist

Chantilly, VA

What Impact You'll Have Our team is charged with taking commercial and academic innovation high ... This project regularly needs various types of people - Data Scientists, Data / ETL Engineers ...

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All JobsData Scientist With Sagemaker Jobs

Data Scientist With Sagemaker information

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$122.7K

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How much do data scientist with sagemaker jobs pay per year?

As of Aug 14, 2026, the average yearly pay for data scientist with sagemaker in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is a data scientist with SageMaker?

A Data Scientist with SageMaker is a professional who leverages Amazon SageMaker, a cloud-based machine learning platform, to build, train, and deploy machine learning models at scale. They are skilled in data analysis, statistical modeling, and using SageMaker's tools for tasks such as data preprocessing, model selection, and automated machine learning (AutoML). These data scientists streamline workflows by taking advantage of SageMaker's integrated Jupyter notebooks, managed training, and deployment services to deliver insights and predictive solutions efficiently.

How does a data scientist with SageMaker typically collaborate with engineering and DevOps teams?

As a Data Scientist utilizing SageMaker, you will frequently collaborate with engineering and DevOps teams to ensure that your machine learning models are seamlessly integrated into production environments. This involves sharing model artifacts, working together on deployment pipelines, and optimizing cloud resource usage. Clear communication is essential, as you'll need to explain model requirements and performance metrics to technical stakeholders. Collaboration often includes conducting code reviews, troubleshooting deployment issues, and participating in discussions about scalability and security within AWS infrastructure.

What is the difference between Data Scientist With Sagemaker vs Data Scientist?

AspectData Scientist With SagemakerData Scientist
Required SkillsMachine learning, AWS Sagemaker, Python, data analysisData analysis, machine learning, Python, R, SQL
Work EnvironmentCloud-based platforms, AWS ecosystemOn-premises or cloud, various platforms
CertificationsAWS certifications beneficialData science certifications (e.g., CAP, DASCA)
Industry UsageTech, finance, healthcare using AWSBroad across industries

While both roles involve data analysis and machine learning, Data Scientist With Sagemaker specializes in deploying models using AWS Sagemaker, focusing on cloud-based solutions. In contrast, Data Scientist roles are broader, covering various tools and platforms. The Sagemaker role emphasizes cloud skills and AWS certifications, making it ideal for cloud-centric organizations.

What are the key skills and qualifications needed to thrive as a data scientist with SageMaker?

To thrive as a Data Scientist with SageMaker, you need strong skills in statistics, machine learning, programming (Python, R), and a solid background in data analysis, typically supported by a relevant degree. Mastery of AWS SageMaker, cloud platforms, version control tools, and certifications like AWS Certified Machine Learning are highly valued. Excellent problem-solving, communication, and the ability to work collaboratively set outstanding professionals apart in this role. These skills are crucial for building, deploying, and explaining scalable machine learning models that deliver real business value.
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Data Scientist With Sagemaker jobs near you
Infographic showing various Data Scientist With Sagemaker job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Data Scientist

Ztek Consulting INC

Charlotte, NC • On-site

Contractor

Re-posted 25 days ago

Job description

Role Name: Data Scientist

Location: Charlotte, NC / hybrid

Type of hire: Contract

JOB DESCRIPTION:

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 AIML 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 AWSKey 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 AIML 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