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Key Responsibilities AI & Machine Learning Development Develop text-based models and process both structured and unstructured data.
Design and implement machine learning and deep learning models for specific business applications.
Improve machine learning algorithms to enhance performance and accuracy.
Apply deep learning frameworks such as TensorFlow and PyTorch to build and deploy neural networks.
Data Management & Feature Engineering Manage and process large datasets, including cleaning, transforming, and extracting relevant features for model training.
Ensure data accuracy, consistency, and reliability through data quality checks and validation.
Develop and implement methods to improve data integrity, efficiency, and overall data quality.
MLOps, Deployment & Monitoring Use MLOps tools and practices to monitor, optimize, and deploy AI solutions.
Develop A/B Testing mechanisms, model quality assessments, and hypothesis validation.
Evaluate machine learning models and ensure they meet performance expectations.
Technical Support & Collaboration Translate business data needs into clear technical system requirements.
Provide training and technical support to end users on how to effectively use machine learning models.
Collaborate with cross-functional teams including business analysts and IT specialists to ensure smooth integration of advanced analytics.
Documentation & Security Prepare all required technical documentation according to organizational standards.
Implement security measures to protect sensitive data and manage appropriate access levels for machine learning systems and models.
Innovation & Continuous Improvement Evaluate and recommend new tools and methods that enhance AI and machine learning capabilities.
Support advanced analytics initiatives to uncover innovative insights.
Qualifications Bachelor’s degree in Computer Science, Artificial Intelligence, Data Analytics, or related field.
4+ years of experience in machine learning and deep learning.
Certifications in data analytics or machine learning systems.
Practical experience with: SAS Dataiku Experience in both public and private sectors, preferably within Saudi Arabia .
Strong background in data analytics and delivering multiple projects in the same field.
Ability to work collaboratively with multi-functional teams to ensure seamless integration of advanced analytics.
Required Skills Strong expertise in ML and deep learning algorithms.
Excellent data analysis and feature engineering skills.
Strong understanding of MLOps frameworks.
Excellent communication skills and the ability to produce high-quality technical documentation.
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