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Data Scientist With Sagemaker Jobs (NOW HIRING)

Advance Auto Parts, Inc.

Data Scientist

Raleigh, NC · On-site

Role Summary We are seeking an experienced Data Scientist with strong expertise in Data Science ... ML Tooling: 5+ years experience with SageMaker (training, processing, pipelines, model registry ...

Advance Auto Parts

Data Scientist

Raleigh, NC · On-site +1

Role Summary We are seeking an experienced Data Scientist with strong expertise in Data Science ... ML Tooling: 5+ years experience with SageMaker (training, processing, pipelines, model registry ...

Inizio Partners

Data Scientist

Dallas, TX

$90K - $110K/hr

About the Job The Data Science team partners with marketing, analytics, and digital optimization ... with AWS analytics and machine learning tools, including Amazon Redshift and AWS SageMaker. * 0-3 ...

V2Soft

Data Scientist

Seattle, WA

Only W2, No C2C - Onsite We are seeking a Data Scientist with a strong background in marketing ... Familiarity with cloud computation (e.g., AWS tools such as S3, SageMaker, EMR, or EC2)

Augment

Principal Scientist, Data

Houston, TX

$80 - $83/hr

Data Scientist - AI/ML Focus Worksite: Onsite Monday-Thursday (Mandatory) - Houston, TX Must-Have ... Experience with Snowflake , AWS (SageMaker, S3, Redshift), and automated ML pipelines. * Strong ...

SWBC

Senior Data Scientist

San Antonio, TX

The Senior Data Scientist will serve as a subject matter expert and strategic partner to business ... AWS SageMaker, Bedrock, and S3. * Experience with MLOps tools and practices, including MLflow ...

SWBC

Senior Data Scientist

San Antonio, TX · On-site

The Senior Data Scientist will serve as a subject matter expert and strategic partner to business ... AWS SageMaker, Bedrock, and S3. * Experience with MLOps tools and practices, including MLflow ...

Swbc

Senior Data Scientist

San Antonio, TX · On-site

The Senior Data Scientist will serve as a subject matter expert and strategic partner to business ... AWS SageMaker, Bedrock, and S3. * Experience with MLOps tools and practices, including MLflow ...

Marencor

Data Scientist with Python

Dallas, TX · On-site

Data Scientist with Python Location: Dallas, TX below. Data Science Skills * Deploy and maintain knowledge ingestion pipelines and integration into API-based services. * Strong knowledge of data ...

Datum Software, Inc.

Data Scientist

Charlotte, NC

Design and implement endtoend machine learning ML pipelines using services such as Amazon SageMaker ... Collaborate with data engineers to design ETL pipelines and ensure data availability and ...

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 ...

V2Soft

Data Scientist

Seattle, WA · On-site

They are seeking a Data Scientist with a strong background in marketing measurement and ... with cloud computation (e.g., AWS tools such as S3, SageMaker, EMR, or EC2) • Experience ...

neptune technologies

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 ...

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Data Scientist With Sagemaker information

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$37.5K

$122.7K

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

As of Jun 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 working 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, and why are they important?

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.
More about Data Scientist With Sagemaker jobs
What cities are hiring for Data Scientist With Sagemaker jobs? Cities with the most Data Scientist With Sagemaker job openings:
What states have the most Data Scientist With Sagemaker jobs? States with the most job openings for Data Scientist With Sagemaker jobs include:
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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 June 2026, with employment types broken down into 2% Locum Tenens, 5% As Needed, 88% Full Time, 2% Temporary, 2% Contract, and 1% Nights. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Data Scientist

Data Scientist

Advance Auto Parts, Inc.

Raleigh, NC • On-site

Full-time

Posted 18 days ago

Job description

Job Description
Role Summary
We are seeking an experienced Data Scientist with strong expertise in Data Science, machine learning engineering with hands on experience in designing and deploying ML solutions in production. This role focuses on building scalable ML solutions, productionizing models, and enabling robust ML platforms for enterprise-grade deployments.
This role is a hybrid work model (4 days in office, 1 day work from home) based out of our corporate headquarters located in Raleigh, NC
Key Responsibilities
  • Build ML Models: Design and implement predictive and prescriptive models for regression, classification, and optimization problems.Apply advanced techniques such as structural time series modeling and boosting algorithms (e.g., XGBoost, LightGBM).
  • Train and Tune Models: Develop and tune machine learning models using Python, PySpark, TensorFlow, and PyTorch.
  • Collaboration & Communication: Work closely with stakeholders to understand business challenges and translate them into data science solutions and work in the end-to-end solutioning. Collaborate with cross-functional teams to ensure successful integration of models into business processes.
  • Monitoring & Visualization: Rapidly prototype and test hypotheses to validate model approaches. Build automated workflows for model monitoring and performance evaluation. Create dashboards using tools like Databricks and Palantir to visualize key model metrics like model drift, Shapley values etc.
  • Productionize ML: Build repeatable paths from experimentation to deployment (batch, streaming, and low-latency endpoints), including feature engineering, training, evaluation,
  • Own ML Platform: Stand up and operate core platform components-model registry, feature store, experiment tracking, artifact stores, and standardized CI/CD for ML.
  • Pipeline Engineering: Author robust data/ML pipelines (orchestrated with Step Functions / Airflow / Argo) that train, validate, and release models on schedules or events.
  • Observability & Quality: Implement end-to-end monitoring, data validation, model/drift checks, and alerting SLA/SLOs.
  • Governance & Risk: Enforce model/version lineage, reproducibility, approvals, rollback plans, auditability, and cost controls aligned to enterprise policies.
  • Partner & Mentor: Collaborate with on-shore/off-shore teams; coach data scientists on packaging, testing, and performance; contribute to standards and reviews.
  • Hands-on Delivery: Prototype new patterns; troubleshoot production issues across data, model, and infrastructure layers.

Required Qualifications
  • Education: Bachelor's degree in Computer Science, Information Technology, Data Science, or Mathematics, Statistics or related field. MS Preferred.
  • Programming: 5+ years experience with Python (pandas, PySpark, scikit-learn; familiarity with PyTorch/TensorFlow helpful), bash, experience with Docker.
  • ML Experimentation: Design and implement predictive and prescriptive models for regression, classification, and optimization problems. Apply advanced techniques such as structural time series modeling and boosting algorithms (e.g., XGBoost, LightGBM).
  • ML Tooling: 5+ years experience with SageMaker (training, processing, pipelines, model registry, endpoints) or equivalents (Kubeflow, MLflow/Feast, Vertex, Databricks ML).
  • Pipelines & Orchestration: 5+ years' experience with Databricks DABS or Airflow or Step Functions, e-driven designs with EventBridge/SQS/Kinesis.
  • Cloud Foundations: 3+ years experience with AWS/Azure/GCP on various services like ECR/ECS, Lambda, API Gateway, S3, Glue/Athena/EMR, RDS/Aurora (PostgreSQL/MySQL), DynamoDB, CloudWatch, IAM, VPC, WAF. GCP experience is preferred.
  • Snowflake Foundations: Warehouses, databases, schemas, stages, Snowflake SQL, RBAC, UDF, Snowpark.
  • CI/CD: 3+ years hands-on experience with CodeBuild/Code Pipeline or GitHub Actions/GitLab; blue/green, canary, and shadow deployments for models and services.
  • Feature Pipelines: Proven experience with batch/stream pipelines, schema management, partitioning, performance tuning; parquet/iceberg best practices.
  • Testing & Monitoring: Unit/integration tests for data and models, contract tests for features, reproducible training; data drift/performance monitoring.
  • Operational Mindset: Incident response for model services, SLOs, dashboards, runbooks; strong debugging across data, model, and infra layers.
  • Soft Skills: Clear communication, collaborative mindset, and a bias to automate & document.
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age national origin, religion, sexual orientation, gender identity, status as a veteran and basis of disability or any other federal, state or local protected class. We comply with all applicable federal, state, and local laws.
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https://jobs.advanceautoparts.com/us/en/disclosures
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About Advance Auto Parts

Sourced by ZipRecruiter

At Advance Auto Parts we have a passion for YES. Each day we are motivated by a passion to help our Customers. We have a commitment to advance the lives of our fellow Team Members, Customers, and the Communities where we live and work.

Industry

Motor vehicle and motor vehicle parts wholesalers, retail, internet and it and elementary and secondary schools

Company size

10,000+ Employees

Headquarters location

Raleigh, NC, US

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