Data Scientist

Master-Works; Riyadh; On-site; SAR 180,000 - 240,000; Full time

Job summary

Master Works is a Saudi technology company seeking a Data Scientist to design and develop advanced machine learning models and analytics solutions to solve complex business challenges. You will work closely with business and technical stakeholders to transform data into actionable insights and scalable solutions.

The role requires 2+ years of experience in data science, strong Python and SQL skills, and familiarity with ML frameworks.

Qualifications

• Bachelor’s degree or higher in data science or a related field.
• 2+ years of professional experience in data science or ML.
• Strong Python and SQL proficiency with data preprocessing skills.

Responsibilities

• Design, develop, test, and deploy ML models and analytics solutions.
• Extract, process, and analyze large datasets from multiple sources.
• Perform EDA to identify trends and actionable insights.
• Develop and maintain ML pipelines for production environments.
• Collaborate with stakeholders to translate requirements into DS solutions.
• Apply statistical modeling and ML techniques to business problems.
• Evaluate model performance and scalability, optimizing where needed.
• Research and evaluate new data science tools and methodologies.

Skills

Python

SQL

R

Data Science

Communication

Problem Solving

Education

Bachelor's or higher in Data Science or related

Tools

R

Job description

Master Works is a Saudi technology company driving digital transformation through emerging technologies and innovative digital solutions. We empower organizations with expertise across data management, AI, software development, and digital strategy, contributing to the digital economy in line with Saudi Vision 2030.

Master works is seeking a skilled Data Scientist to design and develop advanced machine learning models, predictive analytics solutions, and data-driven approaches to solve complex business challenges. The successful candidate will work closely with business and technical stakeholders to transform data into actionable insights and scalable solutions.

Key Responsibilities

• Design, develop, test, and deploy machine learning models and predictive analytics solutions.
• Extract, process, and analyze large and complex datasets from multiple sources.
• Perform exploratory data analysis (EDA) to identify trends, patterns, and actionable insights.
• Develop and maintain robust statistical and machine learning pipelines for production environments.
• Collaborate with stakeholders and business teams to understand requirements and translate them into data science solutions.
• Apply statistical modeling and machine learning techniques to address business problems.
• Evaluate and optimize model performance, accuracy, and scalability.
• Research and evaluate emerging data science tools, techniques, and methodologies.
• Present data-driven findings and recommendations to both technical and non-technical stakeholders.

Required Qualifications & Skills

• Bachelor’s degree or higher in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.
• 2+ years of professional experience in Data Science, Machine Learning, or a related field.
• Strong proficiency in Python; knowledge of R is a plus.
• Advanced SQL skills and experience working with large datasets.
• Strong understanding of machine learning, statistical modeling, and predictive analytics.
• Experience with data preprocessing, feature engineering, model evaluation, and optimization.
• Experience deploying machine learning models or analytical solutions into production environments.
• Strong analytical, problem-solving, and communication skills.
• Ability to work effectively with cross-functional teams and translate business requirements into technical solutions.

Preferred Qualifications

• Experience with cloud platforms, big data technologies, or ML/AI frameworks.
• Familiarity with MLOps and production machine learning practices.
• Experience working in an enterprise or business-focused environment.