Expert Data Scientist

Master-Works; Riyad Al Khabra; On-site; SAR 200,000 - 300,000; Full time

Job summary

A leading tech company in Saudi Arabia is seeking an Expert Data Scientist responsible for developing advanced AI and machine learning models. This role requires 5+ years in Data Science and fluency in Arabic. Candidates should have strong skills in Python and a deep understanding of machine learning methodologies. The role includes responsibilities such as data analysis, solution implementation, and technical project support. This is an exciting opportunity for someone passionate about AI and data-driven solutions.

Qualifications

• 5+ years experience in Data Science, AI, or Machine Learning.
• Deep knowledge of machine learning and data science methodologies.
• Experience working with large datasets and implementing data mining techniques.

Responsibilities

• Develop advanced AI and machine learning models.
• Perform complex data analysis.
• Design end-to-end AI solutions.
• Support technical teams in delivering data-driven initiatives.

Skills

Machine learning methodologies

Fluent Arabic

Python

Data analysis

Data visualization (Power BI, Tableau)

Education

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

Tools

TensorFlow

PyTorch

Scikit-learn

Pandas

NumPy

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.