DATAEXL INFORMATION LLC

Data Scientist

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist/ML/LLM Engineer, requiring 6-18 months of W2 employment in Charlotte, NC or Jersey City, NJ (3 days onsite weekly). Key skills include Python, R, TensorFlow, and Linux. Open-source product experience is essential.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
December 4, 2025
🕒 - Duration
More than 6 months
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🏝️ - Location
On-site
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
Charlotte, NC
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🧠 - Skills detailed
#AI (Artificial Intelligence) #Storage #Alation #Scala #Python #Version Control #Consulting #Keras #Linux #Theano #Jupyter #Cloud #Data Science #R #TensorFlow #Security #Compliance #ML (Machine Learning)
Role description
Only W2 No C2C, No H1B, No OPT, NO CPT Title: Data Scientist/ML/LLM Engineer Location: charlotte, NC or Jersey city, NJ(3 Days onsite a week) Duration: 6-18 Months Specific Technical Requirements – Firm understanding of open source products, the skill set of team needed to support consulting needs on Linux, Ubuntu, and Cloud. Python, Anaconda, Jupyter Notebook, R, RStudio, R Shiny, R Markdown, TensorFlow, Keras, H2O, Theano, Caffe, etc. Job Description: The Data Science ML/LLM engineer operational enhancements, maintenance and support of the all the data science software in our Innovation Lab (Python, R, TensorFlow, H2O, Keras, etc. This includes providing security management, application and underlying infrastructure support (OS, Storage, Applications, Web and Database) and ensuring processes are aligned with tactical and strategic information management initiatives. The Data Science ML/LLM engineer serves as liaison between the enterprise infrastructure support teams and risk business partners to ensure appropriate delivery of technology solutions in accordance with business requirements and objectives. The Data Science ML/LLM engineer also ensures the AI solutions are positioned for compliance with IT policies and standards and agreed upon service levels. Primary Responsibilities: • Ensures the overall health of the Data Science environment/solutions • Applies maintenance releases, upgrades, version control of packages, and hot fixes as required • Designs solutions to reduce the operational and management complexity of the platform • Designs, implements, and maintains AI Solutions via Red Hat Enterprise Linux, Ubuntu, and Cloud. • Performs platform capacity planning and management • Serves as an escalation point for escalated platform issues. • Establishes best practices and guidelines for usage of the Data Science platforms