Enterprise Solutions Inc.
Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist in Phoenix, AZ (Hybrid) with a contract length of "unknown" and a pay rate of "unknown." Key skills include Python, R, and ML/Ops. Industry experience in AI governance and compliance is essential.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
416
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🗓️ - Date
March 18, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Hybrid
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Phoenix, AZ
-
🧠 - Skills detailed
#Monitoring #R #AI (Artificial Intelligence) #ML (Machine Learning) #Cloud #Python #Data Science #Kubernetes #GitHub #Compliance #Documentation #Deployment
Role description
Data Scientist
Phoenix AZ (Hybrid).
Role Summary
Data Scientist responsible for translating business requirements into actionable insights, independently developing machine learning models, designing end-to-end MLOps pipelines, and ensuring AI governance and compliance for deployed solutions.
Must Have: Python, R , ML/OPS
Key Responsibilities
• Gather and understand business requirements; convert them into analytical solutions aligned with business objectives.
• Develop, validate, and optimize statistical, probabilistic, and traditional ML models independently.
• Design and implement end-to-end MLOps pipelines including CI/CD (GitHub Actions) and cloud deployments using Kubernetes.
• Manage model lifecycle including deployment, monitoring, retraining, and versioning.
• Ensure AI governance, compliance, model documentation, explainability, and audit readiness for existing and new models.
• Collaborate with onshore/offshore teams to ensure clear ownership and timely delivery.
• Provide regular progress updates and present solutions to clients and stakeholders.
• Mentor junior data scientists and promote best practices.
Data Scientist
Phoenix AZ (Hybrid).
Role Summary
Data Scientist responsible for translating business requirements into actionable insights, independently developing machine learning models, designing end-to-end MLOps pipelines, and ensuring AI governance and compliance for deployed solutions.
Must Have: Python, R , ML/OPS
Key Responsibilities
• Gather and understand business requirements; convert them into analytical solutions aligned with business objectives.
• Develop, validate, and optimize statistical, probabilistic, and traditional ML models independently.
• Design and implement end-to-end MLOps pipelines including CI/CD (GitHub Actions) and cloud deployments using Kubernetes.
• Manage model lifecycle including deployment, monitoring, retraining, and versioning.
• Ensure AI governance, compliance, model documentation, explainability, and audit readiness for existing and new models.
• Collaborate with onshore/offshore teams to ensure clear ownership and timely delivery.
• Provide regular progress updates and present solutions to clients and stakeholders.
• Mentor junior data scientists and promote best practices.
