Data Scientist

Company Overview

Circlys is an innovative fintech enterprise headquartered in Riyadh, Saudi Arabia, focused on transforming traditional rotating savings and credit associations (ROSCA), branded as Circle. Their secure and authorized platform supports over 3 million users and has facilitated savings exceeding SAR 8 billion. Circlys leads the market with a culture grounded in innovation, collaboration, and operational mastery.

Role Summary

The Data Scientist will be tasked with crafting, deploying, and refining machine learning models to address complex business challenges such as forecasting, classification, and recommendation systems. Reporting within an on-site role in Riyadh, the candidate will analyze intricate datasets using statistical techniques and predictive analytics to glean actionable insights that guide strategic decisions. This position requires a blend of advanced technical skills in Python, SQL, and ML frameworks paired with clear communication capabilities for diverse audiences.

Primary Responsibilities

• Create and implement machine learning solutions targeting business problems like prediction, classification, and recommendations.
• Conduct exploratory data analysis to detect key patterns and trends.
• Maintain thorough documentation covering methodologies, assumptions, and outcomes to ensure reproducibility.
• Process and analyze substantial structured and unstructured data collections.
• Partner with engineering units to operationalize models and embed them within existing pipelines.
• Develop informative dashboards and visual presentations tailored for a range of stakeholders.
• Perform A/B experiments and apply statistical methods to assess business strategies.
• Observe and enhance model performance through ongoing monitoring and retraining as necessary.
• Continuously update knowledge regarding emerging trends, tools, and best practices in data science and machine learning.

Required Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related disciplines.
• Two to four years of relevant professional experience in data science, ML engineering, or analytics.
• Strong programming skills in Python or R for analytical processing and modeling.
• Proficient in SQL and experienced with relational database systems.
• Practical expertise with ML libraries and frameworks such as scikit-learn, TensorFlow, PyTorch, and XGBoost.
• Good understanding of statistical principles, probability theory, and experimental design including A/B testing.
• Familiarity with data visualization tools like Tableau, Power BI, matplotlib, or seaborn.
• Experience working within version control systems, especially Git, supporting collaborative projects.

Preferred Skills and Experiences

• Knowledge of big data ecosystems including Spark and Hadoop.
• Exposure to MLOps tools and methodologies such as MLflow, Airflow, Docker, and Kubernetes.
• Practical experience with NLP, computer vision, or deep learning technologies.
• Familiarity with Agile or Scrum development frameworks.

Soft Skills

• Excellent communication skills for conveying complex ideas to non-technical individuals.
• Strong analytical abilities and a curious, problem-solving mindset.
• Capability to operate independently as well as collaborate within diverse teams.

Recommended Certifications (Optional)

• Google Professional Data Engineer
• Microsoft Azure Data Scientist Associate (DP-100)
• AWS Certified Machine Learning – Specialty
• IBM Data Science Professional Certificate
• Certified Analytics Professional (CAP)
• TensorFlow Developer Certificate
• SAS Certified Data Scientist
• Deep Learning Specialization (DeepLearning.AI)