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Data Science/Machine Learning Builder

Donato Technologies, IncMinnetonka, MN

$60 - $64 / hour

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Overview

Remote
On-site
Compensation
$60-$64/hour

Job Description

Data Science/Machine Learning Builder
Minnetonka, Minnesota (Day 1 Onsite GC/Citizen only)

Job Description:

  • Client seeks a highly skilled Data Science / Machine Learning Builder to drive advanced analytics, anomaly detection, predictive modeling, and production-grade AI solutions across Claims and Payment Integrity, Customer Service, and Technology workflows.
  • This role emphasizes hands-on delivery of scalable, secure, and maintainable ML systems in a healthcare context, with a focus on multimodal approaches, deep learning, and integration into enterprise workflows.
  • The ideal candidate will possess strong technical ownership, production mindset, and the ability to translate complex business problems into robust analytical solutions.
  • The position is based in Minnetonka, Minnesota, with hybrid work expectations and a preference for local talent.

Roles and Responsibilities:

  • Data Science / Machine Learning Builder, Production AI Systems Developer, Design, build, deploy, and operate production AI, machine learning, and analytical systems with a focus on claims integrity, customer service, and technology workflows.
  • Develop and integrate multimodal systems combining structured data, NLP, embeddings, deep learning, and generative AI for enhanced decision-making and output explainability.
  • Engineer robust feature pipelines, population/target definitions, model evaluation frameworks, and scoring architectures with strong emphasis on explainability, monitoring, and drift detection.
  • Collaborate with MLOps, data engineering, and platform teams to ensure CI/CD, observability, security, compliance, and auditability of deployed models and services.
  • Own operational support for ML systems, including troubleshooting, root-cause analysis, and continuous improvement in production environments.
  • Apply modern software engineering practices including source control, automated testing, infrastructure as code, containers, and deployment automation.
  • Conduct data discovery, curation, and integration work, including diagnosing and resolving pipeline issues where necessary.
  • Work closely with AI/Automation and business teams to design end-to-end solutions that deliver measurable operational and business outcomes.
  • Demonstrate autonomy in ambiguous environments, make sound technical tradeoffs, and deliver high-velocity, reviewable work.

Donato Technologies Inc. is a trusted IT staffing, consulting, and software development partner headquartered in Dallas, Texas. We support clients across industries by understanding their unique business needs and delivering tailored technology and workforce solutions. Our focus is on connecting the right talent with the right opportunity-ensuring clients receive dependable, skilled professionals and candidates receive meaningful career growth and support. We work closely with small to mid-sized organizations to provide flexible, high-quality services that drive performance, innovation, and long-term success.

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FAQs About Data Science/Machine Learning Builder Jobs at Donato Technologies, Inc

What is the work location for this position at Donato Technologies, Inc?
This job at Donato Technologies, Inc is located in Minnetonka, MN, according to the details provided by the employer. Some roles may also include multiple work locations depending on the requirement.
What pay range can candidates expect for this role at Donato Technologies, Inc?
Candidates can expect a pay range of $60–$64 per hour for this role.
What employment applies to this position at Donato Technologies, Inc?
The employer has not provided this information. This may be discussed during the hiring process.
What is the process to apply for this position at Donato Technologies, Inc?
You can apply for this role at Donato Technologies, Inc either through Sonara's automated application system, which helps you submit applications 10X faster with minimal effort, or by applying manually using the direct link on the job page.