Position Overview:

As a Data Analysis and Artificial Intelligence Specialist, you will shape Zein Global’s data ecosystem and develop advanced machine learning, deep learning, and artificial intelligence algorithms to extract actionable insights that can drive the company’s operations. Additionally, you will manage advanced data analysis and modeling projects that leverage big data platforms (Hadoop, Spark) and cloud-based AI solutions to contribute to the company’s business strategies.

Responsibilities:

Big Data Management and Processing:
Process large datasets using big data processing platforms such as Apache Hadoop and Apache Spark, and establish data processing infrastructure.
Analyze data in parallel and at scale using Data Lakes and Distributed File Systems (HDFS).
Develop ETL (Extract, Transform, Load) processes and manage data flows using tools like Apache Kafka and Apache Flink.
Collect and process large data sets from database management systems (SQL and NoSQL), especially working with NoSQL databases like Cassandra, HBase, MongoDB.
Machine Learning and Deep Learning (AI/ML):
Apply deep learning algorithms (such as CNN, RNN, LSTM, GANs) to large datasets and develop customized model solutions based on specific application areas.
Optimize decision support systems using advanced AI methodologies like Reinforcement Learning and Self-supervised Learning.
Use Transfer Learning and Fine-tuning techniques to enhance model development efficiency and speed.
Ensure the best model performance through model development, hyperparameter optimization, grid search, and random search.
Develop deep solutions in areas such as Natural Language Processing (NLP) and Computer Vision (CV).
Data Mining and Advanced Analytics:
Run Anomaly Detection and Outlier Detection algorithms on large datasets to improve business processes.
Utilize advanced data mining techniques like Clustering, Dimensionality Reduction (PCA, t-SNE), and Association Rule Mining to extract meaningful data.
Create predictive models for sales, customer behavior, and process forecasting using Predictive Analytics.
Use Graph Databases to perform complex relationship analysis and derive insights from social network data.
Cloud-Based AI and Data Solutions:
Utilize cloud-based platforms such as AWS Sagemaker, Google AI Platform, and Azure Machine Learning to analyze data, build models, and deploy solutions.
Manage machine learning model workflows using containerization and orchestration tools like Kubeflow, Docker, and Kubernetes.
Scale and sustain AI and data analysis solutions using Serverless Computing.
Data Security and Privacy:
Implement advanced encryption, authentication, anonymization, and data privacy techniques for data security.
Develop AI solutions that ensure data privacy using distributed learning methods like Federated Learning.
Work on data verification and secure data sharing solutions using Blockchain technology.
Data Visualization and Advanced Reporting:
Create advanced dashboards and visualizations using tools like Tableau, Power BI, and D3.js.
Develop Real-Time Dashboards to enable businesses to analyze live data.
Optimize reporting processes using Predictive Reporting and KPI Optimization, making them more proactive.

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