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Data Scientist With Sagemaker Jobs in Iowa (NOW HIRING)

Kellton

Imaging Data Scientist

Johnston, IA · On-site

$75/hr

Imaging Data Scientist Location: Johnston, IA 50131 Locals only within 50-mile required onsite T/W ... Solutions will be developed primarily in Python, integrated with our repositories and workflow ...

Accenture

Senior Data Scientist

Des Moines, IA · On-site

With these new opportunities come increased risks. We work with leading organizations to ensure AI ... Mentor data scientists and other practitioners and contribute to reusable frameworks, standards ...

State of Iowa

Data Scientist 2

Des Moines, IA · On-site

$99K - $142K/yr

... Scientist 2 to join our team! This role is responsible for overseeing the strategic vision ... Manage large-scale data sharing initiatives with key partners including the Judicial Branch ...

New

Vermeer

Data Scientist - R&D (AI/ML)

Ames, IA · On-site

$90 - $120/hr

We're looking for an experienced data scientist who thrives in a fast paced, hands-on team.What You ... Experience with machine learning operations, data modeling concepts, and data storage technologies ...

State of Iowa

Data Scientist 2

Des Moines, IA · Hybrid

$99K - $142K/yr

... Scientist 2to join our team. This role is responsible for overseeing the strategic vision ... Manage large-scale data sharing initiatives with key partners including the Judicial Branch ...

Wellmark

Data Science Associate

Des Moines, IA · On-site

$57K - $58K/yr

Collaborate with team and key business stakeholders to ensure critical business objectives are met ... Specific exposure with hands-on data analysis of databases and files using SQL dialects and ...

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Data Scientist With Sagemaker information

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.

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

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Data Scientist With Sagemaker jobs near you
Infographic showing various Data Scientist With Sagemaker job openings in Iowa as of July 2026, with employment types broken down into 1% As Needed, 81% Full Time, 15% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Imaging Data Scientist

Kellton

Johnston, IA • On-site

$75/hr

Other

Re-posted 21 days ago

Job description

Imaging Data Scientist
Location: Johnston, IA 50131 Locals only within 50-mile required onsite T/W/TH each week
Duration: 12 months + extensions
Max Pay Rate: $75/hr W2 (No Benefits) - DOE

No C2C at this time

Project Scope and Brief Description

Work at the intersection of plant cell biology and applied AI to build, productionize, and maintain computer vision pipelines that accelerate Doubled Haploid (DH) breeding in Biotechnology. The contractor will contribute to endtoend imaging and analytics from microscopy microspore detection to macroscopic structure assessment and plantlet characterization supporting decisions that reduce cycle time and cost in DH programs. Solutions will be developed primarily in Python, integrated with our repositories and workflow tooling, and aligned with Biotech strategy initiatives

Responsibilities:

  • Design & deliver deep learning-based CV models for microscopy and macroscopic assays (detection, segmentation, classification) with measurable accuracy, robustness, and throughput.
  • Build productionready pipelines in Python (data ingest, preprocessing, augmentation, inference, batch processing), integrated with GitLab repos and experiment tracking; ensure reproducibility and documentation.
  • Implement hyperspectral analysis workflows (band selection, normalization, feature extraction, model training).
  • Harmonize imaging acquisition with analysis by collaborating with biology teams to standardize microscopy/RGB/hyperspectral capture and file formats (e.g., FIJI/ImageJ for zstacks; autoscale practices).
  • Quantify model performance (precision/recall, F1, ROC/AUC, calibration) and write clear reports/posters for DH sessions; support factchecking in presentations.
  • Operationalize at scale: batch processing of tens of thousands of structures/images; optimize inference (e.g., torch.compile, mixed precision) and monitor resource usage.
  • Partner with DH stakeholders (biotech & breeding, Genome Technology Discovery, Data Science) to align deliverables with deployment milestones.
  • Maintain IP & data stewardship practices consistent with internal strategy; avoid disclosure of confidential protocols while enabling model reuse

Must Have:

  • 4 6 years handson in computer vision with Python (PyTorch/TensorFlow), including detection/segmentation/classification for scientific or industrial imaging.
  • Proven ability to productionize models: Git/GitLab, code reviews, CICD basics, experiment tracking (MLFlow or equivalent), reproducible data/experiments, and clear documentation.
  • Experience with microscopy image processing, multipage TIFFs, zstacks, autoscale/normalization, and image quality challenges.
  • Familiarity with hyperspectral or multispectral imaging pipelines (preprocessing, dimensionality reduction, modeling) applied to plant or biological materials.
  • Track record of measurable model performance reporting and communicating results via posters/presentations for technical audiences.

NicetoHave

  • Vision Transformers (ViT) and modern YOLO workflows for microscopy/macroscopic tasks; comfort with infer tooling.
  • Experience optimizing inference (e.g., torch.compile, mixed precision) and scaling batch workflows.
  • Domain familiarity with Biotech breeding workflows.
  • Collaboration with discovery and strategy teams; ability to work across biology, engineering, and data science groups.

Soft Skills

  • Strong stakeholder communication and the ability to translate biology & process constraints into CV requirements; comfortable triaging and prioritizing rapidly in active programs.
  • Ownership mindset around documentation, reproducibility, and IPaware sharing.
  • Curious and learning mindset
  • Technical leadership experience

Apply