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Data Scientist With Sagemaker Jobs in Springfield, MO

GRVTY

Technical Scientist - SME

Springfield, MO · On-site +1

$150K - $235K/yr

Familiarity with multi-data stream ingest and analysis techniques. * Working knowledge of the TCPED ... Master's degree in Image Science, Engineering, Applied Physics, Applied Mathematics, or a related ...

Guida's Dairy

Principal Scientist

Springfield, MO

Utilize sensory science tools, available in the Innovation Center, to give data points to the ... Partner with sales to understand customer's future needs, their brands, and strategies to ...

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Data Scientist With Sagemaker information

See Springfield, MO salary details

$34.1K

$111.6K

$178.7K

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

As of Sep 12, 2026, the average yearly pay for data scientist with sagemaker in Springfield, MO is $111,646.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,600.00 and $123,700.00 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.

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.

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 popular job titles related to Data Scientist With Sagemaker jobs in Springfield, MO?

For Data Scientist With Sagemaker jobs in Springfield, MO, the most frequently searched job titles are:

What job categories do people searching Data Scientist With Sagemaker jobs in Springfield, MO look for?

The top searched job categories for Data Scientist With Sagemaker jobs in Springfield, MO are:

Data Scientist With Sagemaker jobs near you
Infographic showing various Data Scientist With Sagemaker job openings in Springfield, MO as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $111,646 per year, or $53.7 per hour.

Sr. Manager, Data Science & Applied AI

Springfield, MO • On-site

O'Reilly Auto Parts
Individual, Family and Community Social Assistance • 10K+ employees
Learn more about O'Reilly Auto Partsexternal

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 12 days ago

O'Reilly Auto Parts rating

5.2

Company rating: 5.2 out of 10

Based on 1,920 frontline employees who took The Breakroom Quiz

Job description

The Sr. Manager, Data Science & Applied AI is a strategic and technical leader responsible for leading Data Science and Applied AI capabilities across multiple business domains, including People Analytics, Inventory Optimization, Supply Chain, Operations, and Generative AI.
This leader will manage and develop high-performing Data Science teams while establishing the strategy and technical direction for Machine Learning, Applied AI, Generative AI, and advanced analytics solutions. The role partners closely with business, product, data engineering, architecture, and technology leaders to translate complex business opportunities into scalable AI-driven solutions with measurable business outcomes.
The ideal candidate combines strong AI/ML and GenAI technical depth with retail business acumen, particularly across Inventory, Supply Chain, Store Operations, Merchandising, Workforce/People Analytics, and other operational functions.
This is an on-site position located in Springfield, MO. Remote work is not an option for this role.
Key Responsibilities
  • Lead multiple Data Science and Applied AI teams supporting business domains such as People Analytics, Inventory Optimization, Supply Chain, Operations, and Generative AI.
  • Define and execute the enterprise strategy for Applied AI, Machine Learning, Generative AI, predictive analytics, and optimization across supported business domains.
  • Identify high-value business opportunities where AI can improve inventory availability, forecasting, replenishment, supply chain efficiency, workforce effectiveness, operational productivity, customer experience, and decision-making.
  • Drive the development and productionization of GenAI solutions, including enterprise copilots, intelligent assistants, RAG-based applications, agentic AI workflows, natural-language analytics, and knowledge-driven automation.
  • Establish standards for LLM evaluation, grounding, guardrails, responsible AI, security, observability, model monitoring, and human-in-the-loop controls.
  • Partner with Data Engineering, Architecture, and Platform teams to establish scalable MLOps and LLMOps capabilities using GCP, Vertex AI, and enterprise data platforms.
  • Lead advanced Data Science capabilities including forecasting, optimization, recommendation systems, predictive modeling, experimentation, segmentation, anomaly detection, and simulation/What-If modeling.
  • Ensure AI/ML solutions are built with production-grade engineering standards, including scalability, reliability, monitoring, data quality, automated testing, reproducibility, and lifecycle management.
  • Establish measurable KPIs and ROI frameworks that connect model performance to business outcomes and financial value.
  • Translate complex model outputs and AI capabilities into actionable recommendations and compelling narratives for executive and business leadership.
  • Build strong partnerships with senior leaders across Inventory, Supply Chain, Store Operations, HR/People Analytics, Merchandising, Digital, and Technology.
  • Lead portfolio prioritization based on business value, feasibility, strategic alignment, and implementation effort.
  • Develop Data Science leaders and individual contributors through coaching, technical mentorship, career development, and succession planning.
  • Stay ahead of emerging developments in Generative AI, Agentic AI, Machine Learning, optimization, and retail technology, and determine where they can create meaningful enterprise value.
  • Own resource planning, vendor strategy, budget management, delivery risks, and execution across the Data Science and Applied AI portfolio.

Required Skills:
  • Proven leadership experience managing Data Science, Machine Learning, or Applied AI teams, preferably across multiple business domains.
  • Strong expertise in Machine Learning, Applied AI, Generative AI, optimization, predictive modeling, and advanced analytics.
  • Hands-on understanding of modern GenAI architectures, including LLMs, RAG, embeddings/vector search, AI agents, prompt engineering, model evaluation, guardrails, and LLMOps.
  • Strong experience with enterprise cloud AI platforms, preferably GCP and Vertex AI.
  • Experience designing and operationalizing scalable MLOps/LLMOps architectures and production AI solutions.
  • Demonstrated ability to connect AI/ML initiatives to measurable operational and financial outcomes.
  • Strong understanding of data engineering, data quality, governance, security, and enterprise data architecture required to support AI at scale.
  • Proven ability to influence senior executives and translate ambiguous business challenges into a prioritized portfolio of Data Science and AI initiatives.
  • Strong people leadership experience, including hiring, developing, coaching, and retaining Data Science and AI talent.
  • Excellent executive communication, storytelling, stakeholder management, and organizational leadership skills.

Preferred:
  • Retail industry experience, particularly within large-scale, multi-channel or store-based retail environments.
  • Deep business understanding of Inventory Management, Inventory Optimization, Demand Forecasting, Replenishment, Supply Chain, Distribution, and Store Operations.
  • Experience applying AI/ML to retail use cases such as demand forecasting, inventory optimization, assortment, pricing, workforce optimization, customer personalization, and operational decision-making.
  • Experience leading People Analytics/Data Science initiatives such as workforce planning, retention, engagement, labor optimization, and talent analytics.
  • Experience delivering Generative AI and Agentic AI solutions from experimentation through production.
  • Experience driving organizational adoption and change management around AI-enabled ways of working.
  • Experience partnering with Product, Engineering, Data, and Business organizations to move AI solutions from POC to production and measurable business value.

Education: Master's Degree or Equivalent Level
Experience: Wide and deep experience providing expert competence (Over 10 years to 15 years)
Managerial Experience: Experience of planning and managing resources to deliver predetermined objectives as specified by more senior managers (Over 3 years to 6 years)
O'Reilly Auto Parts has a proven track record of growth and stability. O'Reilly is full of successful career stories and believes in a strong promote-from-within philosophy, encouraging you to grow your career along with the organization.
Total Compensation Package:
  • Competitive Wages & Paid Time Off
  • Stock Purchase Plan & 401k with Employer Contributions Starting Day One
  • Medical, Dental, & Vision Insurance with Optional Flexible Spending Account (FSA)
  • Team Member Health/Wellbeing Programs
  • Tuition Educational Assistance Programs
  • Opportunities for Career Growth

O'Reilly Auto Parts is an equal opportunity employer. The Company does not discriminate on the basis of race, religion, color, national origin or ancestry (including immigration status or citizenship), sex, sexual orientation, gender identity, pregnancy (including childbirth, lactation, and related medical conditions,) age (40 and over), veteran status, uniformed service member status, physical or mental disability, genetic information (including testing or characteristics) or another protected status as defined by local, state, or federal law, as applicable.
Qualified individuals with a disability may be entitled to reasonable accommodation under the Americans with Disabilities Act. If you require a reasonable accommodation during the application or employment process, please send an email to: rar@oreillyauto.com or call (800) 471-7431 option , and provide your requested accommodation, and position details.

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