Expert Data Scientist

Master-Works; Al Khobar; On-site; SAR 120,000 - 150,000; Full time

Job summary

A leading AI solutions company in Al Khobar is seeking an Expert Data Scientist to develop advanced AI and machine learning models. Your responsibilities will include data analysis, solution implementation, and technical project support. You should have a bachelor's degree in Computer Science or a related field and at least 5 years of experience in data science or AI. Fluent Arabic is mandatory for this role, which promises to be impactful and challenging in a fast-growing field.

Qualifications

• 5+ years of experience in Data Science, AI, or Machine Learning.
• Deep knowledge of machine learning and data science methodologies.
• Familiarity with the end-to-end AI development lifecycle.

Responsibilities

• Develop and validate machine learning and AI models.
• Deploy models into production environments.
• Provide expert consultation on AI solutions and model design.
• Document modeling processes and prepare technical reports.

Skills

Machine learning methodologies

Data analysis

Fluent Arabic

Python

MLOps concepts

Visualization tools

Education

Bachelor’s degree in Computer Science, AI, or related field

Tools

TensorFlow

PyTorch

Scikit-learn

Power BI

Tableau

Job description

Role Summary

The Expert Data Scientist is responsible for developing advanced AI and machine learning models, performing complex data analysis, designing end-to-end AI solutions, and supporting technical teams in delivering data-driven initiatives. The role requires strong technical expertise, analytical depth, and the ability to translate data into impactful solutions.

Key Responsibilities

1. Data Analysis & Modeling

• Collect, clean, transform, and analyze data from different sources.
• Perform exploratory data analysis (EDA) to identify trends and patterns.
• Design, develop, and validate machine learning and AI models.
• Select appropriate algorithms and techniques for each use case.
• Evaluate model performance using industry-standard metrics (Accuracy, Precision, Recall, F1, AUC).
• Optimize and fine-tune models to enhance performance.

2. Solution Implementation

• Deploy machine learning models into production environments.
• Collaborate with Data Engineers and MLOps engineers on pipelines and deployment workflows.
• Build scalable data pipelines for processing large datasets.
• Monitor and update deployed models to ensure continuous performance.

3. Technical Project Support

• Provide expert consultation on AI solutions and model design.
• Identify required data sources and support the data acquisition process.
• Participate in technical discussions with clients and internal teams.
• Support User Acceptance Testing (UAT) from a technical perspective.

4. Documentation & Reporting

• Document modeling processes, methodologies, and analytical results.
• Prepare technical reports and present findings clearly to technical and non-technical audiences.
• Maintain proper documentation for model design and deployment.

Requirements

Language Requirement: Fluent Arabic (mandatory)
Experience Level: 5+ years in Data Science / AI / Machine Learning
Sector: AI projects, digital transformation, advanced analytics
Education: Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Statistics, or a related field

Preferred Certifications:

• Machine Learning / Deep Learning
• Data Science Certifications
• AI & ML specializations

Required Skills & Expertise

• Deep knowledge of machine learning, deep learning, and data science methodologies.
• Strong proficiency in:
  • Python (essential)
• Experience with ML and data libraries:
  • TensorFlow or PyTorch
  • Scikit-learn
  • Pandas, NumPy
• Hands‑on experience with visualization tools:
  • Power BI, Tableau
• Understanding of MLOps concepts and data engineering fundamentals.
• Experience working with large datasets and implementing data mining techniques.

Preferred Experience

• Previous experience in Saudi Arabia (public or private sector).
• Experience in AI projects involving vision, NLP, or sensor data.
• Familiarity with end-to-end AI development lifecycle.