Job Title: Senior Data Scientist

Location: Saudi Arabia, Riyadh (on site)

Duration: 2 years

Role Summary:

We are looking for a Senior Data Scientist to lead the development and deployment of advanced analytics and machine learning solutions that solve high-impact business problems. The ideal candidate is highly skilled in extracting insights from large datasets, building predictive models, and driving data-informed decisions. This hands-on role involves close collaboration with data engineers, domain experts, and business stakeholders to turn data into actionable intelligence.

Key Responsibilities:

• Lead end-to-end data science initiatives: from problem framing, data acquisition, exploration, and modeling to deployment and impact measurement.
• Clean, explore, and transform raw data from various sources to support modeling and analytics.
• Design and implement machine learning and statistical models for tasks such as prediction, classification, segmentation, and anomaly detection.
• Optimize models through feature engineering, hyperparameter tuning, and evaluation techniques.
• Conduct experimental analysis (e.g., A/B testing) to validate hypotheses and improve model performance.
• Define and implement data collection strategies and work with engineering teams to establish scalable data pipelines.
• Translate complex analytical results into clear business recommendations and communicate them effectively to stakeholders.
• Create visualizations and dashboards to track model performance and business KPIs.
• Stay current with emerging machine learning and advanced analytics trends and apply best practices to ongoing projects.
• Mentor junior team members and contribute to the growth of data science capabilities.
• Preferred Qualifications:
• 6+ years of hands-on experience in data science, including building and deploying machine learning models in production environments.
• Strong proficiency in Python and ML libraries such as Pandas, Scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Solid foundation in statistics, data modeling, and experimental design.
• Experience working with deep learning frameworks and applications.
• Experience working with time series, sensor, or geospatial data
• Exposure to computer vision projects or image/video data is a strong plus.
• Understanding of MLOps and model lifecycle management.
• Skilled in data visualization tools such as Power BI, Tableau, or Plotly.
• Experience with cloud platforms and distributed data is a plus.
• Strong analytical thinking, communication skills, and business acumen.