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Data Curation Ai Machine Learning Jobs in Oklahoma

micro1 AI

Computational Biologist - AI Reviewer

Norman, OK · On-site +1

$90 - $120/hr

No prior experience in AI is required -- your domain knowledge is what matters. Scope of Work ... Contribute to the refinement of data curation methodologies and best practices in computational ...

micro1 AI

Computational Biologist - AI Reviewer

Tulsa, OK · On-site +1

$90 - $120/hr

No prior experience in AI is required -- your domain knowledge is what matters. Scope of Work ... Contribute to the refinement of data curation methodologies and best practices in computational ...

micro1 AI

Computational Biologist - AI Reviewer

Edmond, OK · On-site +1

$90 - $120/hr

No prior experience in AI is required -- your domain knowledge is what matters. Scope of Work ... Contribute to the refinement of data curation methodologies and best practices in computational ...

Pwc

AI & GenAI Data Scientist-Director

Tulsa, OK · On-site

$155K - $410K/yr

Responsibilities - Leading the design and development of AI and Machine Learning solutions to transform raw data into actionable insights - Overseeing the implementation of data infrastructure and ...

Pwc

AI & GenAI Data Scientist-Director

Oklahoma City, OK · On-site

$155K - $410K/yr

Responsibilities - Leading the design and development of AI and Machine Learning solutions to transform raw data into actionable insights - Overseeing the implementation of data infrastructure and ...

AAON, Inc.

Data and Analytics AI Engineer

Tulsa, OK

$104K - $125K/yr

The Data and Analytics AI Engineer is responsible for designing, building, and supporting ... Support development and deployment of AI, machine learning, and generative AI solutions as the ...

AAON, Inc.

Data and Analytics AI Engineer

Tulsa, OK · On-site

$104K - $125K/yr

The Data and Analytics AI Engineer is responsible for designing, building, and supporting ... Support development and deployment of AI, machine learning, and generative AI solutions as the ...

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Data Curation Ai Machine Learning information

What are the key skills and qualifications needed to thrive as a data curation AI machine learning specialist?

To thrive as a Data Curation AI Machine Learning Specialist, you need strong data management skills, a background in computer science or data science, and experience with machine learning principles. Familiarity with programming languages like Python or R, data labeling tools, and database systems, as well as certifications in machine learning or data engineering, are typically required. Attention to detail, critical thinking, and effective communication stand out as essential soft skills for managing complex datasets and collaborating with cross-functional teams. These skills ensure high-quality, well-organized data that drives accurate machine learning models and reliable AI outcomes.

What is a data curation AI machine learning specialist?

A Data Curation AI/Machine Learning specialist is a professional who manages, organizes, and prepares large datasets to be used in artificial intelligence and machine learning projects. They ensure that data is accurate, relevant, and accessible, often cleaning and labeling data so it can be effectively used to train machine learning models. Their role bridges the gap between raw data sources and the teams building AI solutions, enabling more reliable and efficient model development. They may also work with data governance, privacy, and compliance issues to ensure data quality and security.

What are some common challenges faced by data curation professionals working in AI and machine learning projects?

One of the key challenges data curation specialists encounter in AI and machine learning is ensuring the quality and consistency of large, diverse datasets. This often involves dealing with missing, incomplete, or biased data, which can impact model performance. Additionally, data curators must navigate evolving data privacy regulations and work closely with data scientists, engineers, and domain experts to align data preparation with project goals. Effective communication and a meticulous approach are crucial for maintaining data integrity and supporting robust machine learning outcomes.

What is the difference between Data Curation Ai Machine Learning vs Data Analyst?

AspectData Curation Ai Machine LearningData Analyst
Primary FocusPreparing and managing data for AI and ML modelsAnalyzing data to generate business insights
Skills RequiredData management, programming, understanding of AI/ML algorithmsStatistical analysis, data visualization, Excel, SQL
Tools UsedPython, R, SQL, data cleaning toolsExcel, Tableau, SQL, statistical software
Work EnvironmentData science teams, AI/ML projects, tech companiesBusiness departments, analytics teams, consulting firms

While Data Curation Ai Machine Learning specialists focus on preparing data for AI and machine learning models, Data Analysts interpret data to support business decisions. Both roles require strong data skills but differ in their primary objectives and tools used.

What are popular job titles related to Data Curation Ai Machine Learning jobs in Oklahoma?

For Data Curation Ai Machine Learning jobs in Oklahoma, the most frequently searched job titles are:

What job categories do people searching Data Curation Ai Machine Learning jobs in Oklahoma look for?

The top searched job categories for Data Curation Ai Machine Learning jobs in Oklahoma are:

What cities in Oklahoma are hiring for Data Curation Ai Machine Learning jobs?

Cities in Oklahoma with the most Data Curation Ai Machine Learning job openings:

Data Curation Ai Machine Learning jobs near you

AI/Automation Architect

Norman Regional Health System

Norman, OK • On-site

Full-time

Re-posted 25 days ago

Norman Regional Health System rating

7.4

Company rating: 7.4 out of 10

Based on 56 frontline employees who took The Breakroom Quiz

270th of 887 rated healthcare providers

Job description

Job Summary
The AI & Automation Architect is responsible for designing the end-to-end technical strategy for the organization's intelligent automation initiatives. This role involves selecting the right mix of technologies (RPA, Generative AI, Machine Learning, IDP) to solve complex business problems. The Architect ensures that solutions are scalable, secure, and cost-effective, moving beyond simple task automation to full-scale process transformation.
  • Design scalable architectures for intelligent automation solutions, integrating RPA bots with AI models (e.g., using LLMs for decision-making within an RPA workflow)
  • Evaluate and select appropriate platforms and tools based on cost, security, and fit
  • Define how automation tools communicate with enterprise systems via APIs, webhooks, or database connections
  • Establish coding standards, reusable component libraries, and best practices for development teams to ensure consistency
  • Work with InfoSec to ensure all AI/automation workflows comply with data privacy laws (GDPR/CCPA/HIPAA) and internal security policies (e.g., PII masking, role-based access control)
  • Oversee the infrastructure sizing to support bots and high-volume AI inference requests
  • Collaborate with business analysts to determine if a process should be automated and how
  • Lead rapid Proof of Concept (PoC) projects to test emerging technologies before enterprise rollout
  • Design the "Control Room" strategy for monitoring bot health, AI model drift, and license utilization
  • Disaster Recovery: Create failover strategies to ensure business-critical automations continue running during system outages

Typical Duties:
  • Meeting with Health system leaders to analyze a proposed process and determining if it requires simple RPA, complex AI (e.g., OCR/NLP), or if it shouldn't be automated at all
  • Drafting technical blueprints that detail exactly how a bot will log in, where data will be stored, how exceptions are handled, and which AI models will be called
  • Researching and testing new AI tools to see if they fit the health systems tech stack better than current tools
  • Designing and documenting the REST/SOAP API integrations between the automation platform and third-party apps
  • Calculating the necessary compute power (CPU/RAM/GPU) required for upcoming automations and provisioning Virtual Machines (VMs)
  • Configuring "Credential Vaults" so bots can log into systems without exposing passwords in the code
  • Building and maintaining a library of "snippets" that all developers must use to save time
  • Monitors bot health to ensure critical automations ran successfully overnight
  • Troubleshoot complex failures that regular support teams cannot fix
  • Planning and executing upgrades for the automation platform without breaking existing bots
  • Facilitating whiteboard sessions with non-technical departments to uncover their pain points
  • Prompt engineering for business logic, understanding "context windows," and mitigating AI hallucinations in enterprise data.
  • Experience with OCR and data extraction tools.
  • Python, C#/.NET
  • PowerShell or Bash for infrastructure tasks.
  • Ability to design solutions that can handle spikes in volume.
  • Knowledge of load balancing and concurrent processing.
  • Understanding of RBAC (Role-Based Access Control).
  • Secure credential management.
  • Understanding of Virtual Machines (VMs), VDI (Virtual Desktop Infrastructure), and Docker/Kubernetes.
  • Setting up pipelines to automate the testing and deployment of bots.
  • Version control (Git) strategies for automation teams.

Qualifications
Education
  • Bachelor's degree in Computer Science, Data Science, or a related engineering discipline or equivalent experience required.

Licensure/Certification
  • Prefer candidate holds an advanced professional certification in a major automation platform, such as the UiPath Certified Professional Automation Solutions Architect or Microsoft Power Platform Solution Architect

(Above requirements can be met by equivalent combination of education and experience)
Experience
  • 7+ years of IT experience, including at least 4 years designing scalable RPA and intelligent automation solutions using platforms like UiPath or Power Automate
  • Demonstrated expertise in integrating generative AI, machine learning models, and complex APIs into business workflows is essential
  • Proven leadership in guiding technical teams through the full software development lifecycle (SDLC) within an Agile environment is required
  • Experience translating business requirements into technical blueprints and managing stakeholder expectations is critical for success in this role

Work Shift
Day

What Norman Regional Health System employees say

Pay

Benefits

Hours and flexibility

Workplace

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