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Now viewing: Data Scientist / AI & Data Engineering Architect
CI
Cardinal Integrated Technologies Inc
Data Scientist / AI & Data Engineering Architect
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Job Description
We have an onsite contract job opportunity for a Data Scientist / AI & Data Engineering Architect with one of our clients. If interested, please respond to me with the below-required details, or I would appreciate it if you could refer an ex-colleague/team member/friend looking for similar roles. CardinalIT offers a referral bonus of $500 for each such referral, to show gratitude and appreciation for this gesture.
Updated Resume:
Expected rate range W2: Availability to start: I'm looking forward to hearing back from you.
Job Title:
Data Scientist /
AI & Data Engineering Architect Location:
Lake Success, NY (Onsite)
Duration:
6+
Months Job Summary:
We are seeking a skilled Data Scientist / AI Engineer with strong experience in Machine Learning, Artificial Intelligence, Data Science, Azure, and Data Engineering . The ideal candidate will develop and deploy scalable AI/ML solutions, analyze large datasets, and drive business outcomes through data-driven insights.
Key Requirements:
Hands-on experience in Data Science, Machine Learning, and AI. Proven experience developing and deploying ML/AI solutions for business use cases. Strong proficiency in Python, data analysis, and ML frameworks (TensorFlow, PyTorch, Scikit-learn, etc.). Experience with Azure services and Data Engineering technologies. Knowledge of data pipelines, ETL processes, and cloud-based analytics platforms. Excellent communication and stakeholder management skills.
Preferred Skills:
Azure Machine Learning, Databricks, Data Factory, Synapse. MLOps, Generative AI, and Large Language Models (LLMs). SQL, data modeling, and cloud-native architectures. This role requires a blend of AI/ML expertise, cloud technologies, and data engineering skills to deliver innovative and scalable solutions. -- Best Regards, Abhishek Singh | Manager - Recruitment |
Cardinal Integrated Technologies Inc Direct:
+1
Ph:
Ext 337
Email:
Linkedin Url:
707 Alexander Rd, Ste 202 Princeton, NJ 08540 USA .
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